Nothing
## ----include = FALSE----------------------------------------------------------
knitr::opts_chunk$set(
collapse = TRUE,
comment = "#>"
)
## ----eval = FALSE-------------------------------------------------------------
# browseVignettes(package = "mcradds")
## -----------------------------------------------------------------------------
library(mcradds)
## -----------------------------------------------------------------------------
data("qualData")
data("platelet")
data(creatinine, package = "mcr")
data("calcium")
data("ldlroc")
data("PDL1RP")
data("glucose")
data("adsl_sub")
## -----------------------------------------------------------------------------
size_one_prop(p1 = 0.9, p0 = 0.85, alpha = 0.05, power = 0.8)
## -----------------------------------------------------------------------------
size_ci_one_prop(p = 0.85, lr = 0.8, alpha = 0.05, method = "wilson")
## -----------------------------------------------------------------------------
size_ci_one_prop(p = 0.85, lr = 0.8, alpha = 0.05, method = "simple-asymptotic")
## -----------------------------------------------------------------------------
size_corr(r1 = 0.95, r0 = 0.9, alpha = 0.025, power = 0.8, alternative = "greater")
## -----------------------------------------------------------------------------
size_ci_corr(r = 0.9, lr = 0.85, alpha = 0.025, alternative = "greater")
## -----------------------------------------------------------------------------
adsl_sub %>%
descfreq(
var = "AGEGR1",
bygroup = "TRTP",
format = "xx (xx.x%)"
)
## -----------------------------------------------------------------------------
adsl_sub %>%
descfreq(
var = c("AGEGR1", "SEX", "RACE"),
bygroup = "TRTP",
format = "xx (xx.x%)",
addtot = TRUE,
na_str = "0"
)
## -----------------------------------------------------------------------------
adsl_sub %>%
descvar(
var = "AGE",
bygroup = "TRTP"
)
## -----------------------------------------------------------------------------
adsl_sub %>%
descvar(
var = c("AGE", "BMIBL", "HEIGHTBL"),
bygroup = "TRTP",
stats = c("N", "MEANSD", "MEDIAN", "RANGE", "IQR"),
autodecimal = TRUE,
addtot = TRUE
)
## -----------------------------------------------------------------------------
head(qualData)
## -----------------------------------------------------------------------------
tb <- qualData %>%
diagTab(
formula = ~ CandidateN + ComparativeN,
levels = c(1, 0)
)
tb
## -----------------------------------------------------------------------------
dummy <- data.frame(
id = c("1001", "1001", "1002", "1002", "1003", "1003"),
value = c(1, 0, 0, 0, 1, 1),
type = c("Test", "Ref", "Test", "Ref", "Test", "Ref")
) %>%
diagTab(
formula = type ~ value,
bysort = "id",
dimname = c("Test", "Ref"),
levels = c(1, 0)
)
dummy
## -----------------------------------------------------------------------------
# Default method is Wilson score, and digit is 4.
tb %>% getAccuracy(ref = "r")
# Alter the number of digit to 2.
tb %>% getAccuracy(ref = "r", digit = 2)
# Alter the number of digit to 2.
tb %>% getAccuracy(ref = "r", r_ci = "clopper-pearson")
## -----------------------------------------------------------------------------
# When the reference is a comparative assay, not gold standard.
tb %>% getAccuracy(ref = "nr", nr_ci = "wilson")
## -----------------------------------------------------------------------------
# Deming regression
fit <- mcreg(
x = platelet$Comparative, y = platelet$Candidate,
error.ratio = 1, method.reg = "Deming", method.ci = "jackknife"
)
printSummary(fit)
getCoefficients(fit)
## -----------------------------------------------------------------------------
# absolute bias.
calcBias(fit, x.levels = c(30))
# proportional bias.
calcBias(fit, x.levels = c(30), type = "proportional")
## -----------------------------------------------------------------------------
# Default difference type
blandAltman(
x = platelet$Comparative, y = platelet$Candidate,
type1 = 3, type2 = 5
)
# Change relative different type to 4.
blandAltman(
x = platelet$Comparative, y = platelet$Candidate,
type1 = 3, type2 = 4
)
## -----------------------------------------------------------------------------
# ESD approach
ba <- blandAltman(x = platelet$Comparative, y = platelet$Candidate)
out <- getOutlier(ba, method = "ESD", difference = "rel")
out$stat
out$outmat
# 4E approach
ba2 <- blandAltman(x = creatinine$serum.crea, y = creatinine$plasma.crea)
out2 <- getOutlier(ba2, method = "4E")
out2$stat
out2$outmat
## -----------------------------------------------------------------------------
x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c(2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)
pearsonTest(x, y, h0 = 0.5, alternative = "greater")
## -----------------------------------------------------------------------------
x <- c(44.4, 45.9, 41.9, 53.3, 44.7, 44.1, 50.7, 45.2, 60.1)
y <- c(2.6, 3.1, 2.5, 5.0, 3.6, 4.0, 5.2, 2.8, 3.8)
spearmanTest(x, y, h0 = 0.5, alternative = "greater")
## -----------------------------------------------------------------------------
refInterval(x = calcium$Value, RI_method = "parametric", CI_method = "parametric")
## -----------------------------------------------------------------------------
refInterval(x = calcium$Value, RI_method = "nonparametric", CI_method = "nonparametric")
## -----------------------------------------------------------------------------
refInterval(x = calcium$Value, RI_method = "robust", CI_method = "boot")
## -----------------------------------------------------------------------------
# H0 : Difference between areas = 0:
aucTest(x = ldlroc$LDL, y = ldlroc$OxLDL, response = ldlroc$Diagnosis)
## -----------------------------------------------------------------------------
# H0 : Superiority margin <= 0.1:
aucTest(
x = ldlroc$LDL, y = ldlroc$OxLDL, response = ldlroc$Diagnosis,
method = "superiority", h0 = 0.1
)
## -----------------------------------------------------------------------------
# H0 : Non-inferiority margin <= -0.1:
aucTest(
x = ldlroc$LDL, y = ldlroc$OxLDL, response = ldlroc$Diagnosis,
method = "non-inferiority", h0 = -0.1
)
## -----------------------------------------------------------------------------
reader <- PDL1RP$btw_reader
tb1 <- reader %>%
diagTab(
formula = Reader ~ Value,
bysort = "Sample",
levels = c("Positive", "Negative"),
rep = TRUE,
across = "Site"
)
getAccuracy(tb1, ref = "bnr", rng.seed = 12306)
## -----------------------------------------------------------------------------
read <- PDL1RP$wtn_reader
tb2 <- read %>%
diagTab(
formula = Order ~ Value,
bysort = "Sample",
levels = c("Positive", "Negative"),
rep = TRUE,
across = "Sample"
)
getAccuracy(tb2, ref = "bnr", rng.seed = 12306)
## -----------------------------------------------------------------------------
site <- PDL1RP$btw_site
tb3 <- site %>%
diagTab(
formula = Site ~ Value,
bysort = "Sample",
levels = c("Positive", "Negative"),
rep = TRUE,
across = "Sample"
)
getAccuracy(tb2, ref = "bnr", rng.seed = 12306)
## -----------------------------------------------------------------------------
fit <- anovaVCA(value ~ day / run, glucose)
VCAinference(fit)
## -----------------------------------------------------------------------------
object <- blandAltman(x = platelet$Comparative, y = platelet$Candidate)
# Absolute difference plot
autoplot(object, type = "absolute")
# Relative difference plot
autoplot(object, type = "relative")
## -----------------------------------------------------------------------------
autoplot(
object,
type = "absolute",
jitter = TRUE,
fill = "lightblue",
color = "grey",
size = 2,
ref.line.params = list(col = "grey"),
loa.line.params = list(col = "grey"),
label.digits = 2,
label.params = list(col = "grey", size = 3, fontface = "italic"),
x.nbreak = 6,
main.title = "Bland-Altman Plot",
x.title = "Mean of Test and Reference Methods",
y.title = "Reference - Test"
)
## -----------------------------------------------------------------------------
fit <- mcreg(
x = platelet$Comparative, y = platelet$Candidate,
method.reg = "PaBa", method.ci = "bootstrap"
)
autoplot(fit)
## -----------------------------------------------------------------------------
autoplot(
fit,
identity.params = list(col = "blue", linetype = "solid"),
reg.params = list(col = "red", linetype = "solid"),
equal.axis = TRUE,
legend.title = FALSE,
legend.digits = 3,
x.title = "Reference",
y.title = "Test"
)
## ----sessionInfo, echo=FALSE--------------------------------------------------
sessionInfo()
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