tests/testthat/test-expirest_osle.R
In piusdahinden/expirest: Expiry Estimation Procedures
context("Ordinary shelf life estimation")
# The tests use the values published by LeBlond et al. (LeBlond 2011),
# i.e. in the various tables and figures that are presented in
# LeBlond, D., Griffith, D. and Aubuchon, K. Linear Regression 102:
# Stability Shelf Life Estimation Using Analysis of Covariance.
# J Valid Technol (2011) 17(3): 47-68.
test_that("expirest_osle_results_match_LeBlond_2011", {
re <-
expirest_osle(data = exp1[exp1$Batch %in% c("b2", "b5", "b7"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "cics")
expect_equivalent(signif(re[["POI"]]["cics"], 12), 25.9957631369)
expect_equivalent(signif(re[["Intercepts"]][["cics"]]$icpt, 12),
100.566878981)
expect_equivalent(signif(re[["Models"]][["cics"]]$coefficients[2], 12),
-0.192993630573)
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(0.435993484727, 0.228684731019))
expect_equivalent(
signif(summary(re[["Models"]][["cics"]])[["fstatistic"]][1], 12),
129.051417200)
# Results presented in LeBlond 2011
# Table V and Figure 4
# Model Type: cics
# POI: 26
# Regression Equation: y = 100.567 - 0.192994 time
# ANCOVA - F value for Batch: 0.436
# ANCOVA - F value for Batch * Time: 0.229
# Analysis of Variance - F value for Regression: 129.051
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
re <-
expirest_osle(data = exp1[exp1$Batch %in% c("b3", "b4", "b5"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "dics")
expect_equivalent(signif(re[["POI"]]["dics"], 12), 23.3972651235)
expect_equivalent(signif(re[["Intercepts"]][["dics"]]$icpt, 12),
c(102.175653109, 104.255189423, 100.820021871))
expect_equivalent(signif(re[["Models"]][["dics"]]$coefficients[4], 12),
-0.213120866465)
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(21.7380213596, 0.183108926252))
expect_equivalent(
signif(summary(re[["Models"]][["dics"]])[["fstatistic"]][1], 12),
37.0144226385)
# Results presented in LeBlond 2011
# Table VII and Figure 6
# Model Type: dics
# POI: 23.4
# Regression Equations:
# Batch 3: y = 102.176 - 0.213121 time
# Batch 4: y = 104.255 - 0.213121 time
# Batch 5: y = 100.82 - 0.213121 time
# ANCOVA - F value for Batch: 21.738
# ANCOVA - F value for Batch * Time: 0.183
# Analysis of Variance - F value for Regression: 37.0144
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
re <-
expirest_osle(data = exp1[exp1$Batch %in% c("b4", "b5", "b8"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "dids")
expect_equivalent(signif(re[["POI"]]["dids"], 12), 15.8448655130)
expect_equivalent(signif(re[["Intercepts"]][["dids"]]$icpt, 12),
c(104.070645793, 100.781872268, 101.259375000))
expect_equivalent(signif(
c(re[["Models"]][["dids.pmse"]]$coefficients[4],
re[["Models"]][["dids.pmse"]]$coefficients[4] +
re[["Models"]][["dids.pmse"]]$coefficients[5:6]), 12),
c(-0.196151337247, -0.208608547839, -0.330208333333))
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(72.1242158003, 1.95541944320))
expect_equivalent(
signif(summary(re[["Models"]][["dids.pmse"]])[["fstatistic"]][1], 12),
49.8306556826)
# Results presented in LeBlond 2011
# Table IX and Figure 7
# Model Type: dids
# POI: 15.6
# Regression Equations:
# Batch 4: y = 104.071 - 0.196151 time
# Batch 5: y = 100.782 - 0.208609 time
# Batch 8: y = 101.259 - 0.330208 time
# ANCOVA - F value for Batch: 72.124
# ANCOVA - F value for Batch * Time: 1.955
# Analysis of Variance - F value for Regression: 49.831
# Note that the POI of 15.6 is obtained when using the dids model. When
# the POI estimation is based on the models fitted to the individual
# batches, and using the result of the worst case batch, the estimated POI
# is 15.8. This procedure is the one that is used also by SAS JMP. In
# JMP 12.0.1, for this data set the POI is estimated as 15.844877978. The
# result differs from the fifth decimal place. This is due do the fact
# that the POI estimation is based on an iterative method. It is not
# calculated analytically.
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
re <-
expirest_osle(data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "upper")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "dids")
expect_equivalent(signif(re[["POI"]]["dids"], 12), 15.8448655130)
expect_equivalent(signif(re[["Intercepts"]][["dids"]]$icpt, 12),
c(0.027880626223, 0.126543831957, 0.112218750000))
expect_equivalent(signif(
c(re[["Models"]][["dids.pmse"]]$coefficients[4],
re[["Models"]][["dids.pmse"]]$coefficients[4] +
re[["Models"]][["dids.pmse"]]$coefficients[5:6]), 12),
c(0.005884540117, 0.006258256435, 0.009906250000))
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(72.1242158003, 1.95541944320))
expect_equivalent(
signif(summary(re[["Models"]][["dids.pmse"]])[["fstatistic"]][1], 12),
49.8306556826)
# Results presented in LeBlond 2011
# Table XII and Figure 8
# Model Type: dids
# POI: 15.61
# Regression Equations:
# Batch 4: y = 0.0278806 + 0.00588454 time
# Batch 5: y = 0.126544 + 0.00625826 time
# Batch 8: y = 0.112219 + 0.00990625 time
# ANCOVA - F value for Batch: 72.124
# ANCOVA - F value for Batch * Time: 1.955
# Analysis of Variance - F value for Regression: 49.831
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
rel <-
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "lower")
reu <-
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "upper")
# <-><-><-><->
expect_equal(rel[["Model.Type"]]$type.acronym, "cics")
expect_equivalent(signif(rel[["POI"]]["cics"], 12), 50.7665191694)
expect_equivalent(signif(reu[["POI"]]["cics"], 12), 45.3460440833)
expect_equivalent(signif(reu[["Intercepts"]][["cics"]]$icpt, 12),
2.45678204711)
expect_equivalent(signif(reu[["Models"]][["cics"]]$coefficients[2], 12),
0.002272338514)
expect_equal(signif(c(stats::anova(reu[["Models"]][["dids.pmse"]],
reu[["Models"]][["dics"]],
reu[["Models"]][["cics"]])[3, "F"],
stats::anova(reu[["Models"]][["dids.pmse"]],
reu[["Models"]][["dics"]])[2, "F"]), 12),
c(0.353853883257, 0.748152729736))
expect_equivalent(
signif(summary(reu[["Models"]][["cics"]])[["fstatistic"]][1], 12),
0.034723832039)
# Results presented in LeBlond 2011
# Table XIV and Figure 9
# Model Type: cics
# POI: 45.35
# Regression Equations: 2.45678 + 0.0022724
# ANCOVA - F value for Batch: 0.354
# ANCOVA - F value for Batch * Time: 0.748
# Analysis of Variance - F value for Regression: 0.034726
# Note that the value at the sixth decimal place of the F value differs
# from the corresponding value of the calculated value. Thus, the model
# was fitted also in JMP 12.0.1 where the F value was calculated as
# 0.034723832039 which is exactly the same value that was calculated
# here (by R). Therefore, it must be concluded that the results presented
# in LeBlond 2011, Table XIV, must have been obtained with a data set
# that slightly deviates from the data set that is presented in Table XIII.
})
# The tests use the values published in the JMP(R) 12 Reliability and Survival
# Methods manual, i.e. in chapter Degradation, sub-chapter Stability Analysis
# on p. 174-176 of the manual, i.e. in SAS Institute Inc. 2015. JMP(R) 12
# Reliability and Survival Methods. Cary, NC: SAS Institute Inc.
test_that("expirest_osle_results_match_JMP_reliability_and_survival_methods_
manual", {
re <-
expirest_osle(data = exp4, response_vbl = "Conc", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
r_mod <- stats::lm(Conc ~ Month * Batch, data = exp4)
lsl <- 95
tmp <- find_poi(srch_range = c(0, 500), model = r_mod, sl = lsl,
alpha = 0.05, ivl_type = "one.sided",
ivl_side = "lower", ivl = "confidence")
# <-><-><-><->
expect_is(re, "expirest_osle")
expect_equal(re[["Model.Type"]]$type.acronym, "dics")
expect_equivalent(re$wc.batch["dics"], 2)
expect_equivalent(signif(re[["POI"]], 12),
c(29.9856687174, 23.4750503440,
23.2441996167, 23.1159717387))
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["cics"]])[2, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(10.1083606518, 19.8876404032, 0.329080900382))
expect_equivalent(signif(re[["Intercepts"]][["cics"]]$icpt, 12),
101.906446205)
expect_equivalent(signif(re[["Models"]][["cics"]]$coefficients[2], 12),
-0.190871685462)
expect_equivalent(signif(re[["Intercepts"]][["dics"]]$icpt, 12),
c(101.833246643, 100.450143334, 102.066579977,
104.136572391))
expect_equivalent(signif(re[["Models"]][["dics"]]$coefficients[5], 12),
-0.202213553211)
expect_equivalent(signif(re[["Intercepts"]][["dids"]]$icpt, 12),
c(101.817460317, 100.249139280, 102.384126984,
104.070645793))
expect_equivalent(signif(
c(re[["Models"]][["dids.pmse"]]$coefficients[5],
re[["Models"]][["dids.pmse"]]$coefficients[5] +
re[["Models"]][["dids.pmse"]]$coefficients[6:8]), 12),
c(-0.200634920635,
-0.180125195618153, -0.233968253968254, -0.196151337247228))
# Transcription of results shown in Figure 6.27 Stability Models
# The best model accepted at the significance level of 0.25 has Different
# intercepts and Common slopes. The model suggests the earliest crossing
# time at 23.47505 with 95 percent confidence. ICH Guidelines indicate an
# expiration time of 23.47505.
# Display Intercept Slope Earliest Crossing Time
# O Different Different 23.11596
# X Different Common 23.47505
# O Common Common 29.98567
#
# Note that when using the dids model for estimation of the POI as proposed
# in LeBlond 2011, a POI of 23.244185941565 is obtained, i.e. a value that
# is greater. There are examples, though, where the situation is the other
# way round, i.e. where the estimate that is obtained based on the dids
# model results in a smaller POI (see example in LeBlond 2011, Table IX).
# Results from analysis in JMP 12.0.1 software, Degradation platform,
# Stability Test tab
# Worst case batch: 2_12 (from graphical output)
#
# Model Comparisons - F Statistic
# Source Intercept Slope | Intercept Slope F Statistic
# A Different Different | Common Common 10.10836
# B Different Common | Common Common 19.88764
# C Different Different | Different Common 0.329081
#
# Model 1 - Simple Linear Path, Parameter Estimates
# Parameter Estimate
# Intercept[Batch Number=1_11] 101.8175
# Slope[Batch Number=1_11] -0.20063
# Intercept[Batch Number=2_12] 100.2491
# Slope[Batch Number=2_12] -0.18013
# Intercept[Batch Number=3_13] 102.3841
# Slope[Batch Number=3_13] -0.23397
# Intercept[Batch Number=4_14] 104.0706
# Slope[Batch Number=4_14] -0.19615
#
# Model 2 - Simple Linear Path, Parameter Estimates
# Parameter Estimate
# Slope -0.20221
# Intercept[Batch Number=1_11] 101.8332
# Intercept[Batch Number=2_12] 100.4501
# Intercept[Batch Number=3_13] 102.0666
# Intercept[Batch Number=4_14] 104.1366
#
# Model 3 - Simple Linear Path, Parameter Estimates
# Parameter Estimate
# Intercept 101.9064
# Slope -0.19087
#
# Model 1 - Simple Linear Path, Parameter Estimates
# Parameter Batch Number Estimate
# Intercept 1_11 101.8175
# Slope 1_11 -0.20063
# Intercept 2_12 100.2491
# Slope 2_12 -0.18013
# Intercept 3_13 102.3841
# Slope 3_13 -0.23397
# Intercept 4_14 104.0706
# Slope 4_14 -0.19615
})
test_that("expirest_osle_estimation_succeeds_for_poi", {
usl <- 4.5
lsl <- 0.5
tmp <- rep(NA, 8)
# <-><-><-><->
tmp[1] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[2] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[3] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"]
tmp[4] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"]
tmp[5] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "two.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[6] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[7] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "two.sided", ivl_side = "upper")[["POI"]]["cics"]
tmp[8] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "upper")[["POI"]]["cics"]
# <-><-><-><->
expect_equal(signif(tmp, 12),
c(115.468684445, 102.847355846, 96.3055219561, 84.0292339443,
95.4652197782, 79.6924982370, 82.6037890116, 67.2979863914))
})
test_that("expirest_osle_estimation_succeeds_with_transformations", {
tmp <- rep(NA, 7)
# <-><-><-><->
tmp[1] <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("log", "log"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["dids"]
tmp[2] <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("sqrt", "sqrt"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["dids"]
tmp[3] <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 5000),
alpha = 0.05, alpha_pool = 0.25, xform = c("sq", "sq"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["dids"]
tmp[4] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "sq"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "lower"
)[["POI"]]["dids"]
tmp[5] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "lower"
)[["POI"]]["dids"]
tmp[6] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "sq"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"
)[["POI"]]["dids"]
tmp[7] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"
)[["POI"]]["dids"]
# <-><-><-><->
expect_equal(signif(tmp, 12),
c(22.9926049346, 20.3205949274, 14.7086080921, 26.1751174005,
31.8950504925, 37.1116679193, 33.9520528257))
})
test_that("expirest_osle_estimation_succeeds_with_a_single_batch", {
tmp <- rep(NA, 4)
# <-><-><-><->
tmp[1] <-
expirest_osle(
data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 0.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")[["POI"]]["dids"]
tmp[2] <-
expirest_osle(
data = exp3[exp3$Batch == "b2", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 0.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")[["POI"]]["dids"]
tmp[3] <-
expirest_osle(
data = exp3[exp3$Batch == "b3", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 0.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")[["POI"]]["dids"]
tmp[4] <-
expirest_osle(
data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = c(0.5, 4.5),
sl_sf = c(2, 2), srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "both")[["POI"]]["dids"]
# <-><-><-><->
expect_equal(signif(tmp, 12),
c(50.0621475632, 43.7101461304, 199.8917947989, 41.1584877869))
})
test_that("expirest_osle_estimation_succeeds_for_model_type", {
t_dat1 <- exp1[exp1$Batch %in% c("b2", "b5", "b7"), ]
t_dat2 <- exp1[exp1$Batch %in% c("b3", "b4", "b5"), ]
t_dat3 <- exp1[exp1$Batch %in% c("b4", "b5", "b8"), ]
# <-><-><-><->
r_ret1 <-
expirest_osle(
data = t_dat1, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")
r_ret2 <-
expirest_osle(
data = t_dat2, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")
r_ret3 <-
expirest_osle(
data = t_dat3, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")
# <-><-><-><->
expect_equal(r_ret1[["Model.Type"]][[2]], "cics")
expect_equal(r_ret2[["Model.Type"]][[2]], "dics")
expect_equal(r_ret3[["Model.Type"]][[2]], "dids")
expect_equivalent(r_ret1[["Model.Type"]][[1]], c(1, 1))
expect_equivalent(r_ret2[["Model.Type"]][[1]], c(0, 1))
expect_equivalent(r_ret3[["Model.Type"]][[1]], c(0, 0))
})
test_that("expirest_osle_succeeds_for_variables", {
tmp1 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
tmp2 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("log", "log"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
tmp3 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("log", "no"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
tmp4 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "log"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
# <-><-><-><->
expect_equal(tmp1[["response"]], "Related")
expect_equal(tmp1[["time"]], "Month")
expect_equal(tmp1[["batch"]], "Batch")
expect_equal(tmp2[["response"]], "log.Related")
expect_equal(tmp2[["response.orig"]], "Related")
expect_equal(tmp2[["time"]], "log.Month")
expect_equal(tmp2[["time.orig"]], "Month")
expect_equal(tmp2[["batch"]], "Batch")
expect_equal(tmp3[["response"]], "Related")
expect_equal(tmp3[["time"]], "log.Month")
expect_equal(tmp3[["time.orig"]], "Month")
expect_equal(tmp3[["batch"]], "Batch")
expect_equal(tmp4[["response"]], "log.Related")
expect_equal(tmp4[["response.orig"]], "Related")
expect_equal(tmp4[["time"]], "Month")
expect_equal(tmp4[["batch"]], "Batch")
})
test_that("expirest_osle_warns", {
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"Not for all model types POI values obtained.")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(5, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"Not for all model types POI values obtained.")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "two.sided",
ivl_side = "both"),
"Not for all model types POI values obtained.")
expect_warning(
expirest_osle(data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"No POI value was obtained.")
expect_warning(
expirest_osle(data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(5, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"No POI value was obtained.")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 2.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "upper"),
"You specified ivl_side = \"upper\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(2.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "lower"),
"You specified ivl_side = \"lower\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 2.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "upper"),
"You specified ivl_side = \"upper\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 2.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower"),
"You specified ivl_side = \"lower\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "both"),
"ivl_side is specified as \"both\" "
)
})
test_that("expirest_osle_fails_with_warning_tight_spec_limits", {
usl <- 3.5
lsl <- 1.5
tmp <- numeric(2)
# <-><-><-><->
tmp[1] <-
suppressWarnings(
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "lower")[["POI"]]["cics"])
tmp[2] <-
suppressWarnings(
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "upper")[["POI"]]["cics"])
# <-><-><-><->
expect_equal(is.na(tmp[1]), TRUE)
expect_equal(is.na(tmp[2]), TRUE)
})
test_that("expirest_osle_fails_with_warning_tight_uniroot_interval", {
t_dat <- exp1[exp1$Batch %in% c("b2", "b5", "b7"), ]
usl <- 105
lsl <- 95
tmp <- numeric(4)
# <-><-><-><->
tmp[1] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"])
tmp[2] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"])
tmp[3] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"])
tmp[4] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"])
# <-><-><-><->
expect_equal(is.na(tmp[1]), TRUE)
expect_equal(is.na(tmp[2]), TRUE)
expect_equal(is.na(tmp[3]), TRUE)
expect_equal(is.na(tmp[4]), TRUE)
})
test_that("expirest_osle_fails_with_error", {
t_dat <- exp1[exp1$Batch %in% c("b2", "b5", "b7"), ]
t_dal <- t_dat
t_dal$Batch <- as.character(t_dal$Batch)
# <-><-><-><->
expect_error(
expirest_osle(
data = as.matrix(t_dat[, c("Month", "Potency")]),
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"data must be provided as data frame")
expect_error(
expirest_osle(
data = t_dat, response_vbl = 2, time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"response_vbl must be a string")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Mass", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"response_vbl was not found in the provided data frame")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = 3,
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"time_vbl must be a string")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Year",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"time_vbl was not found in the provided data frame")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = 4, sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"batch_vbl must be a string")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Lot", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"batch_vbl was not found in the provided data frame")
expect_error(
expirest_osle(
data = t_dal, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"column in data specified by batch_vbl")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = "sl", sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"sl must be a numeric")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 100, 105), sl_sf = 4,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl must be a numeric or vector of length 1 or 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(105, 95), sl_sf = 4,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl must be of the form")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = "4", srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = -3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 105), sl_sf = 4,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 105), sl_sf = c(4.4, 3.3),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = "alpha",
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"srch_range must be a vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = 500,
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"srch_range must be a vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 5, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = -1, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 5, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha_pool")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = -1, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha_pool")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = "no",
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify xform appropriately")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("yes", "no"),
sf_option = "loose", ivl_type = "one.sided",
shift = c(0, 0), ivl_side = "upper", ivl = "confidence"),
"specify xform appropriately")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "yes"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify xform appropriately")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c("no", "no"), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"shift must be a numeric vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = 1, sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"shift must be a numeric vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "strict", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify sf_option either as \"tight\" or \"loose\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "incorrect",
ivl_type = "one.sided", ivl_side = "upper"),
"specify ivl either as \"confidence\" or \"prediction\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "incorrect", ivl_side = "upper"),
"specify ivl_type either as \"one.sided\" or \"two.sided\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "incorrect"),
"specify ivl_side either as \"lower\", \"upper\" or \"both\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "both"),
"Please provide a specification with two sides.")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 105), sl_sf = c(3, 3),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "two.sided", ivl_side = "both",
rl = c(100, 99, 08)),
"ivl_side must be either \"lower\" or \"upper\"")
})
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context("Ordinary shelf life estimation")
# The tests use the values published by LeBlond et al. (LeBlond 2011),
# i.e. in the various tables and figures that are presented in
# LeBlond, D., Griffith, D. and Aubuchon, K. Linear Regression 102:
# Stability Shelf Life Estimation Using Analysis of Covariance.
# J Valid Technol (2011) 17(3): 47-68.
test_that("expirest_osle_results_match_LeBlond_2011", {
re <-
expirest_osle(data = exp1[exp1$Batch %in% c("b2", "b5", "b7"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "cics")
expect_equivalent(signif(re[["POI"]]["cics"], 12), 25.9957631369)
expect_equivalent(signif(re[["Intercepts"]][["cics"]]$icpt, 12),
100.566878981)
expect_equivalent(signif(re[["Models"]][["cics"]]$coefficients[2], 12),
-0.192993630573)
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(0.435993484727, 0.228684731019))
expect_equivalent(
signif(summary(re[["Models"]][["cics"]])[["fstatistic"]][1], 12),
129.051417200)
# Results presented in LeBlond 2011
# Table V and Figure 4
# Model Type: cics
# POI: 26
# Regression Equation: y = 100.567 - 0.192994 time
# ANCOVA - F value for Batch: 0.436
# ANCOVA - F value for Batch * Time: 0.229
# Analysis of Variance - F value for Regression: 129.051
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
re <-
expirest_osle(data = exp1[exp1$Batch %in% c("b3", "b4", "b5"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "dics")
expect_equivalent(signif(re[["POI"]]["dics"], 12), 23.3972651235)
expect_equivalent(signif(re[["Intercepts"]][["dics"]]$icpt, 12),
c(102.175653109, 104.255189423, 100.820021871))
expect_equivalent(signif(re[["Models"]][["dics"]]$coefficients[4], 12),
-0.213120866465)
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(21.7380213596, 0.183108926252))
expect_equivalent(
signif(summary(re[["Models"]][["dics"]])[["fstatistic"]][1], 12),
37.0144226385)
# Results presented in LeBlond 2011
# Table VII and Figure 6
# Model Type: dics
# POI: 23.4
# Regression Equations:
# Batch 3: y = 102.176 - 0.213121 time
# Batch 4: y = 104.255 - 0.213121 time
# Batch 5: y = 100.82 - 0.213121 time
# ANCOVA - F value for Batch: 21.738
# ANCOVA - F value for Batch * Time: 0.183
# Analysis of Variance - F value for Regression: 37.0144
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
re <-
expirest_osle(data = exp1[exp1$Batch %in% c("b4", "b5", "b8"), ],
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "dids")
expect_equivalent(signif(re[["POI"]]["dids"], 12), 15.8448655130)
expect_equivalent(signif(re[["Intercepts"]][["dids"]]$icpt, 12),
c(104.070645793, 100.781872268, 101.259375000))
expect_equivalent(signif(
c(re[["Models"]][["dids.pmse"]]$coefficients[4],
re[["Models"]][["dids.pmse"]]$coefficients[4] +
re[["Models"]][["dids.pmse"]]$coefficients[5:6]), 12),
c(-0.196151337247, -0.208608547839, -0.330208333333))
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(72.1242158003, 1.95541944320))
expect_equivalent(
signif(summary(re[["Models"]][["dids.pmse"]])[["fstatistic"]][1], 12),
49.8306556826)
# Results presented in LeBlond 2011
# Table IX and Figure 7
# Model Type: dids
# POI: 15.6
# Regression Equations:
# Batch 4: y = 104.071 - 0.196151 time
# Batch 5: y = 100.782 - 0.208609 time
# Batch 8: y = 101.259 - 0.330208 time
# ANCOVA - F value for Batch: 72.124
# ANCOVA - F value for Batch * Time: 1.955
# Analysis of Variance - F value for Regression: 49.831
# Note that the POI of 15.6 is obtained when using the dids model. When
# the POI estimation is based on the models fitted to the individual
# batches, and using the result of the worst case batch, the estimated POI
# is 15.8. This procedure is the one that is used also by SAS JMP. In
# JMP 12.0.1, for this data set the POI is estimated as 15.844877978. The
# result differs from the fifth decimal place. This is due do the fact
# that the POI estimation is based on an iterative method. It is not
# calculated analytically.
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
re <-
expirest_osle(data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "upper")
# <-><-><-><->
expect_equal(re[["Model.Type"]]$type.acronym, "dids")
expect_equivalent(signif(re[["POI"]]["dids"], 12), 15.8448655130)
expect_equivalent(signif(re[["Intercepts"]][["dids"]]$icpt, 12),
c(0.027880626223, 0.126543831957, 0.112218750000))
expect_equivalent(signif(
c(re[["Models"]][["dids.pmse"]]$coefficients[4],
re[["Models"]][["dids.pmse"]]$coefficients[4] +
re[["Models"]][["dids.pmse"]]$coefficients[5:6]), 12),
c(0.005884540117, 0.006258256435, 0.009906250000))
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(72.1242158003, 1.95541944320))
expect_equivalent(
signif(summary(re[["Models"]][["dids.pmse"]])[["fstatistic"]][1], 12),
49.8306556826)
# Results presented in LeBlond 2011
# Table XII and Figure 8
# Model Type: dids
# POI: 15.61
# Regression Equations:
# Batch 4: y = 0.0278806 + 0.00588454 time
# Batch 5: y = 0.126544 + 0.00625826 time
# Batch 8: y = 0.112219 + 0.00990625 time
# ANCOVA - F value for Batch: 72.124
# ANCOVA - F value for Batch * Time: 1.955
# Analysis of Variance - F value for Regression: 49.831
# ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
rel <-
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "lower")
reu <-
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "upper")
# <-><-><-><->
expect_equal(rel[["Model.Type"]]$type.acronym, "cics")
expect_equivalent(signif(rel[["POI"]]["cics"], 12), 50.7665191694)
expect_equivalent(signif(reu[["POI"]]["cics"], 12), 45.3460440833)
expect_equivalent(signif(reu[["Intercepts"]][["cics"]]$icpt, 12),
2.45678204711)
expect_equivalent(signif(reu[["Models"]][["cics"]]$coefficients[2], 12),
0.002272338514)
expect_equal(signif(c(stats::anova(reu[["Models"]][["dids.pmse"]],
reu[["Models"]][["dics"]],
reu[["Models"]][["cics"]])[3, "F"],
stats::anova(reu[["Models"]][["dids.pmse"]],
reu[["Models"]][["dics"]])[2, "F"]), 12),
c(0.353853883257, 0.748152729736))
expect_equivalent(
signif(summary(reu[["Models"]][["cics"]])[["fstatistic"]][1], 12),
0.034723832039)
# Results presented in LeBlond 2011
# Table XIV and Figure 9
# Model Type: cics
# POI: 45.35
# Regression Equations: 2.45678 + 0.0022724
# ANCOVA - F value for Batch: 0.354
# ANCOVA - F value for Batch * Time: 0.748
# Analysis of Variance - F value for Regression: 0.034726
# Note that the value at the sixth decimal place of the F value differs
# from the corresponding value of the calculated value. Thus, the model
# was fitted also in JMP 12.0.1 where the F value was calculated as
# 0.034723832039 which is exactly the same value that was calculated
# here (by R). Therefore, it must be concluded that the results presented
# in LeBlond 2011, Table XIV, must have been obtained with a data set
# that slightly deviates from the data set that is presented in Table XIII.
})
# The tests use the values published in the JMP(R) 12 Reliability and Survival
# Methods manual, i.e. in chapter Degradation, sub-chapter Stability Analysis
# on p. 174-176 of the manual, i.e. in SAS Institute Inc. 2015. JMP(R) 12
# Reliability and Survival Methods. Cary, NC: SAS Institute Inc.
test_that("expirest_osle_results_match_JMP_reliability_and_survival_methods_
manual", {
re <-
expirest_osle(data = exp4, response_vbl = "Conc", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")
r_mod <- stats::lm(Conc ~ Month * Batch, data = exp4)
lsl <- 95
tmp <- find_poi(srch_range = c(0, 500), model = r_mod, sl = lsl,
alpha = 0.05, ivl_type = "one.sided",
ivl_side = "lower", ivl = "confidence")
# <-><-><-><->
expect_is(re, "expirest_osle")
expect_equal(re[["Model.Type"]]$type.acronym, "dics")
expect_equivalent(re$wc.batch["dics"], 2)
expect_equivalent(signif(re[["POI"]], 12),
c(29.9856687174, 23.4750503440,
23.2441996167, 23.1159717387))
expect_equal(signif(c(stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["cics"]])[2, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]],
re[["Models"]][["cics"]])[3, "F"],
stats::anova(re[["Models"]][["dids.pmse"]],
re[["Models"]][["dics"]])[2, "F"]), 12),
c(10.1083606518, 19.8876404032, 0.329080900382))
expect_equivalent(signif(re[["Intercepts"]][["cics"]]$icpt, 12),
101.906446205)
expect_equivalent(signif(re[["Models"]][["cics"]]$coefficients[2], 12),
-0.190871685462)
expect_equivalent(signif(re[["Intercepts"]][["dics"]]$icpt, 12),
c(101.833246643, 100.450143334, 102.066579977,
104.136572391))
expect_equivalent(signif(re[["Models"]][["dics"]]$coefficients[5], 12),
-0.202213553211)
expect_equivalent(signif(re[["Intercepts"]][["dids"]]$icpt, 12),
c(101.817460317, 100.249139280, 102.384126984,
104.070645793))
expect_equivalent(signif(
c(re[["Models"]][["dids.pmse"]]$coefficients[5],
re[["Models"]][["dids.pmse"]]$coefficients[5] +
re[["Models"]][["dids.pmse"]]$coefficients[6:8]), 12),
c(-0.200634920635,
-0.180125195618153, -0.233968253968254, -0.196151337247228))
# Transcription of results shown in Figure 6.27 Stability Models
# The best model accepted at the significance level of 0.25 has Different
# intercepts and Common slopes. The model suggests the earliest crossing
# time at 23.47505 with 95 percent confidence. ICH Guidelines indicate an
# expiration time of 23.47505.
# Display Intercept Slope Earliest Crossing Time
# O Different Different 23.11596
# X Different Common 23.47505
# O Common Common 29.98567
#
# Note that when using the dids model for estimation of the POI as proposed
# in LeBlond 2011, a POI of 23.244185941565 is obtained, i.e. a value that
# is greater. There are examples, though, where the situation is the other
# way round, i.e. where the estimate that is obtained based on the dids
# model results in a smaller POI (see example in LeBlond 2011, Table IX).
# Results from analysis in JMP 12.0.1 software, Degradation platform,
# Stability Test tab
# Worst case batch: 2_12 (from graphical output)
#
# Model Comparisons - F Statistic
# Source Intercept Slope | Intercept Slope F Statistic
# A Different Different | Common Common 10.10836
# B Different Common | Common Common 19.88764
# C Different Different | Different Common 0.329081
#
# Model 1 - Simple Linear Path, Parameter Estimates
# Parameter Estimate
# Intercept[Batch Number=1_11] 101.8175
# Slope[Batch Number=1_11] -0.20063
# Intercept[Batch Number=2_12] 100.2491
# Slope[Batch Number=2_12] -0.18013
# Intercept[Batch Number=3_13] 102.3841
# Slope[Batch Number=3_13] -0.23397
# Intercept[Batch Number=4_14] 104.0706
# Slope[Batch Number=4_14] -0.19615
#
# Model 2 - Simple Linear Path, Parameter Estimates
# Parameter Estimate
# Slope -0.20221
# Intercept[Batch Number=1_11] 101.8332
# Intercept[Batch Number=2_12] 100.4501
# Intercept[Batch Number=3_13] 102.0666
# Intercept[Batch Number=4_14] 104.1366
#
# Model 3 - Simple Linear Path, Parameter Estimates
# Parameter Estimate
# Intercept 101.9064
# Slope -0.19087
#
# Model 1 - Simple Linear Path, Parameter Estimates
# Parameter Batch Number Estimate
# Intercept 1_11 101.8175
# Slope 1_11 -0.20063
# Intercept 2_12 100.2491
# Slope 2_12 -0.18013
# Intercept 3_13 102.3841
# Slope 3_13 -0.23397
# Intercept 4_14 104.0706
# Slope 4_14 -0.19615
})
test_that("expirest_osle_estimation_succeeds_for_poi", {
usl <- 4.5
lsl <- 0.5
tmp <- rep(NA, 8)
# <-><-><-><->
tmp[1] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[2] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[3] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"]
tmp[4] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"]
tmp[5] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "two.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[6] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "lower")[["POI"]]["cics"]
tmp[7] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "two.sided", ivl_side = "upper")[["POI"]]["cics"]
tmp[8] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = usl, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "upper")[["POI"]]["cics"]
# <-><-><-><->
expect_equal(signif(tmp, 12),
c(115.468684445, 102.847355846, 96.3055219561, 84.0292339443,
95.4652197782, 79.6924982370, 82.6037890116, 67.2979863914))
})
test_that("expirest_osle_estimation_succeeds_with_transformations", {
tmp <- rep(NA, 7)
# <-><-><-><->
tmp[1] <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("log", "log"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["dids"]
tmp[2] <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("sqrt", "sqrt"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["dids"]
tmp[3] <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 5000),
alpha = 0.05, alpha_pool = 0.25, xform = c("sq", "sq"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["dids"]
tmp[4] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "sq"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "lower"
)[["POI"]]["dids"]
tmp[5] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "lower"
)[["POI"]]["dids"]
tmp[6] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "sq"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"
)[["POI"]]["dids"]
tmp[7] <-
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 5000), alpha = 0.05, alpha_pool = 0.25,
xform = c("sq", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"
)[["POI"]]["dids"]
# <-><-><-><->
expect_equal(signif(tmp, 12),
c(22.9926049346, 20.3205949274, 14.7086080921, 26.1751174005,
31.8950504925, 37.1116679193, 33.9520528257))
})
test_that("expirest_osle_estimation_succeeds_with_a_single_batch", {
tmp <- rep(NA, 4)
# <-><-><-><->
tmp[1] <-
expirest_osle(
data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 0.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")[["POI"]]["dids"]
tmp[2] <-
expirest_osle(
data = exp3[exp3$Batch == "b2", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 0.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")[["POI"]]["dids"]
tmp[3] <-
expirest_osle(
data = exp3[exp3$Batch == "b3", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 0.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower")[["POI"]]["dids"]
tmp[4] <-
expirest_osle(
data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = c(0.5, 4.5),
sl_sf = c(2, 2), srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "both")[["POI"]]["dids"]
# <-><-><-><->
expect_equal(signif(tmp, 12),
c(50.0621475632, 43.7101461304, 199.8917947989, 41.1584877869))
})
test_that("expirest_osle_estimation_succeeds_for_model_type", {
t_dat1 <- exp1[exp1$Batch %in% c("b2", "b5", "b7"), ]
t_dat2 <- exp1[exp1$Batch %in% c("b3", "b4", "b5"), ]
t_dat3 <- exp1[exp1$Batch %in% c("b4", "b5", "b8"), ]
# <-><-><-><->
r_ret1 <-
expirest_osle(
data = t_dat1, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")
r_ret2 <-
expirest_osle(
data = t_dat2, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")
r_ret3 <-
expirest_osle(
data = t_dat3, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")
# <-><-><-><->
expect_equal(r_ret1[["Model.Type"]][[2]], "cics")
expect_equal(r_ret2[["Model.Type"]][[2]], "dics")
expect_equal(r_ret3[["Model.Type"]][[2]], "dids")
expect_equivalent(r_ret1[["Model.Type"]][[1]], c(1, 1))
expect_equivalent(r_ret2[["Model.Type"]][[1]], c(0, 1))
expect_equivalent(r_ret3[["Model.Type"]][[1]], c(0, 0))
})
test_that("expirest_osle_succeeds_for_variables", {
tmp1 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
tmp2 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("log", "log"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
tmp3 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("log", "no"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
tmp4 <-
expirest_osle(
data = exp2, response_vbl = "Related", time_vbl = "Month",
batch_vbl = "Batch", sl = 0.3, sl_sf = 2, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "log"),
shift = c(1, 0), sf_option = "tight", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["Variables"]]
# <-><-><-><->
expect_equal(tmp1[["response"]], "Related")
expect_equal(tmp1[["time"]], "Month")
expect_equal(tmp1[["batch"]], "Batch")
expect_equal(tmp2[["response"]], "log.Related")
expect_equal(tmp2[["response.orig"]], "Related")
expect_equal(tmp2[["time"]], "log.Month")
expect_equal(tmp2[["time.orig"]], "Month")
expect_equal(tmp2[["batch"]], "Batch")
expect_equal(tmp3[["response"]], "Related")
expect_equal(tmp3[["time"]], "log.Month")
expect_equal(tmp3[["time.orig"]], "Month")
expect_equal(tmp3[["batch"]], "Batch")
expect_equal(tmp4[["response"]], "log.Related")
expect_equal(tmp4[["response.orig"]], "Related")
expect_equal(tmp4[["time"]], "Month")
expect_equal(tmp4[["batch"]], "Batch")
})
test_that("expirest_osle_warns", {
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"Not for all model types POI values obtained.")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(5, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"Not for all model types POI values obtained.")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "two.sided",
ivl_side = "both"),
"Not for all model types POI values obtained.")
expect_warning(
expirest_osle(data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"No POI value was obtained.")
expect_warning(
expirest_osle(data = exp3[exp3$Batch == "b1", ], response_vbl = "Moisture",
time_vbl = "Month", batch_vbl = "Batch", sl = 1.5, sl_sf = 2,
srch_range = c(5, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "prediction", ivl_type = "one.sided",
ivl_side = "lower"),
"No POI value was obtained.")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(0.5, 2.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "upper"),
"You specified ivl_side = \"upper\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(2.5, 4.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "two.sided",
ivl_side = "lower"),
"You specified ivl_side = \"lower\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 2.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "upper"),
"You specified ivl_side = \"upper\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = 2.5, sl_sf = 2,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "lower"),
"You specified ivl_side = \"lower\".")
expect_warning(
expirest_osle(data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = c(1.5, 3.5), sl_sf = c(2, 2),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "tight",
ivl = "confidence", ivl_type = "one.sided",
ivl_side = "both"),
"ivl_side is specified as \"both\" "
)
})
test_that("expirest_osle_fails_with_warning_tight_spec_limits", {
usl <- 3.5
lsl <- 1.5
tmp <- numeric(2)
# <-><-><-><->
tmp[1] <-
suppressWarnings(
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "lower")[["POI"]]["cics"])
tmp[2] <-
suppressWarnings(
expirest_osle(
data = exp3, response_vbl = "Moisture", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "tight", ivl = "prediction",
ivl_type = "two.sided", ivl_side = "upper")[["POI"]]["cics"])
# <-><-><-><->
expect_equal(is.na(tmp[1]), TRUE)
expect_equal(is.na(tmp[2]), TRUE)
})
test_that("expirest_osle_fails_with_warning_tight_uniroot_interval", {
t_dat <- exp1[exp1$Batch %in% c("b2", "b5", "b7"), ]
usl <- 105
lsl <- 95
tmp <- numeric(4)
# <-><-><-><->
tmp[1] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"])
tmp[2] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "lower")[["POI"]]["cics"])
tmp[3] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"])
tmp[4] <-
suppressWarnings(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = lsl, sl_sf = 3, srch_range = c(0, 5),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "prediction",
ivl_type = "one.sided", ivl_side = "upper")[["POI"]]["cics"])
# <-><-><-><->
expect_equal(is.na(tmp[1]), TRUE)
expect_equal(is.na(tmp[2]), TRUE)
expect_equal(is.na(tmp[3]), TRUE)
expect_equal(is.na(tmp[4]), TRUE)
})
test_that("expirest_osle_fails_with_error", {
t_dat <- exp1[exp1$Batch %in% c("b2", "b5", "b7"), ]
t_dal <- t_dat
t_dal$Batch <- as.character(t_dal$Batch)
# <-><-><-><->
expect_error(
expirest_osle(
data = as.matrix(t_dat[, c("Month", "Potency")]),
response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"data must be provided as data frame")
expect_error(
expirest_osle(
data = t_dat, response_vbl = 2, time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"response_vbl must be a string")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Mass", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"response_vbl was not found in the provided data frame")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = 3,
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"time_vbl must be a string")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Year",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"time_vbl was not found in the provided data frame")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = 4, sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"batch_vbl must be a string")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Lot", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"batch_vbl was not found in the provided data frame")
expect_error(
expirest_osle(
data = t_dal, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"column in data specified by batch_vbl")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = "sl", sl_sf = 4, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"sl must be a numeric")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 100, 105), sl_sf = 4,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl must be a numeric or vector of length 1 or 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(105, 95), sl_sf = 4,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl must be of the form")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = "4", srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 105, sl_sf = -3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 105), sl_sf = 4,
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 105), sl_sf = c(4.4, 3.3),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "one.sided", ivl_side = "upper"),
"sl_sf must be a positive integer")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = "alpha",
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"srch_range must be a vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = 500,
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"srch_range must be a vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 5, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = -1, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 5, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha_pool")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = -1, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify alpha_pool")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = "no",
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify xform appropriately")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("yes", "no"),
sf_option = "loose", ivl_type = "one.sided",
shift = c(0, 0), ivl_side = "upper", ivl = "confidence"),
"specify xform appropriately")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "yes"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify xform appropriately")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c("no", "no"), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"shift must be a numeric vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = 1, sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"shift must be a numeric vector of length 2")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "strict", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "upper"),
"specify sf_option either as \"tight\" or \"loose\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "incorrect",
ivl_type = "one.sided", ivl_side = "upper"),
"specify ivl either as \"confidence\" or \"prediction\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "incorrect", ivl_side = "upper"),
"specify ivl_type either as \"one.sided\" or \"two.sided\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "incorrect"),
"specify ivl_side either as \"lower\", \"upper\" or \"both\"")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = 95, sl_sf = 3, srch_range = c(0, 500),
alpha = 0.05, alpha_pool = 0.25, xform = c("no", "no"),
shift = c(0, 0), sf_option = "loose", ivl = "confidence",
ivl_type = "one.sided", ivl_side = "both"),
"Please provide a specification with two sides.")
expect_error(
expirest_osle(
data = t_dat, response_vbl = "Potency", time_vbl = "Month",
batch_vbl = "Batch", sl = c(95, 105), sl_sf = c(3, 3),
srch_range = c(0, 500), alpha = 0.05, alpha_pool = 0.25,
xform = c("no", "no"), shift = c(0, 0), sf_option = "loose",
ivl = "confidence", ivl_type = "two.sided", ivl_side = "both",
rl = c(100, 99, 08)),
"ivl_side must be either \"lower\" or \"upper\"")
})
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