Nothing
context("agree_nest")
testthat::test_that("examples from Zou", {
data("reps")
reps2 = reps
reps2$y[5] = 6.35
reps2$y[9] = 4.09
nest_test = agree_nest(x="x",y="y",
id = "id",
data = reps2,
TOST = FALSE)
nest_test2 = agree_nest(x="x",y="y",
id = "id",
data = reps2,
TOST = FALSE,
prop_bias = TRUE)
nest_test_new = agreement_limit(x="x",y="y",
id = "id",
data = reps2,
data_type = "nest",
alpha = .025)
expect_error(agreement_limit(x="x",y="y",
#id = "id",
data = reps2,
data_type = "nest",
alpha = .025))
nest_test_new2 = agreement_limit(x="x",y="y",
id = "id",
data = reps2,
data_type = "nest",
alpha = .025,
prop_bias = TRUE)
testthat::expect_equal(nest_test_new$loa$bias,0.7234979,
tolerance = .0001)
ch1 = check(nest_test_new)
nest_test_newlog = agreement_limit(x="x",y="y",
id = "id",
data = reps2,
data_type = "nest",
log_tf =TRUE)
nest_test_bland = agreement_limit(x="x",y="y",
id = "id",
data = reps2,
data_type = "nest",
log_tf =TRUE,
loa_calc = "b")
print(nest_test_bland)
agree_test_newlog = agreement_limit(x="x",y="y",
id = "id",
data = reps2,
data_type = "simple",
log_tf =TRUE)
ptest = plot(nest_test_new)
ptest = plot(nest_test_new,
delta = 5)
ptest = plot(nest_test_new,
geom = "geom_bin2d")
ptest = plot(nest_test_new,
geom = "geom_density_2d")
ptest = plot(nest_test_new,
geom = "geom_density_2d_filled")
ptest = plot(nest_test_new,
geom = "stat_density_2d")
print(nest_test_new2)
ptest = plot(nest_test_new2)
ptest = plot(nest_test_new2,
delta = 5)
ptest = plot(nest_test_new2,
geom = "geom_bin2d")
ptest = plot(nest_test_new2,
geom = "geom_density_2d")
ptest = plot(nest_test_new2,
geom = "geom_density_2d_filled")
ptest = plot(nest_test_new2,
geom = "stat_density_2d")
# Ensure emmeans working appropriately
testthat::expect_equal(agree_test_newlog$loa$lower.CL,-0.02185209,
tolerance = .0001)
testthat::expect_equal(nest_test_newlog$loa$df,3,
tolerance = .01)
testthat::expect_equal(!is.null(nest_test_newlog$loa), TRUE)
testthat::expect_equal(nrow(nest_test_newlog$loa), 1)
testthat::expect_equal(nest_test_newlog$loa$lower.CL,-0.319,
tolerance = .001)
testthat::expect_equal(nest_test_newlog$loa$bias,0.1138129,
tolerance = .0001)
testthat::expect_equal(nest_test_newlog$loa$lme,1.030285,
tolerance = .0001)
testthat::expect_equal(class(nest_test_newlog), "loa")
pr1 = print(nest_test_newlog)
nest_test2_new = agreement_limit(x="x",y="y",
id = "id",
data = reps2,
prop_bias = TRUE,
data_type = "nest")
ptest = plot(nest_test2)
ptest = plot(nest_test2_new)
ptest = plot(nest_test_new)
nest_test3_ccc = agree_nest(x="x",y="y",
id = "id",
data = reps2,
TOST = FALSE,
prop_bias = TRUE,
ccc = FALSE)
nest_test3 = agree_nest(x="x",y="y",
id = "id",
data = reps2,
TOST = FALSE,
prop_bias = TRUE)
ptest = plot(nest_test3)
nest_test3 = agree_nest(x="x",y="y",
id = "id",
data = reps,
TOST = FALSE,
delta = 5,
prop_bias = TRUE)
ptest = plot(nest_test3)
testthat::expect_equivalent(nest_test$loa$estimate,
c(.7255,-2.14,3.59),
tolerance = 0.001)
testthat::expect_equivalent(c(nest_test_new$loa$bias,
nest_test_new$loa$lower_loa,
nest_test_new$loa$upper_loa),
c(.7255,-2.14,3.59),
tolerance = 0.005)
testthat::expect_equivalent(c(nest_test_new$loa$lower_loa_ci,
nest_test_new$loa$upper_loa_ci),
c(-9.8,11.2),
tolerance = 0.01)
testthat::expect_equivalent(nest_test$loa$lower.ci[2:3],
c(-9.83,1.77),
tolerance = 0.01)
testthat::expect_equivalent(nest_test$loa$upper.ci[2:3],
c(-.33,11.27),
tolerance = 0.01)
nest_test = agree_nest(x="x",y="y",
delta = 2,
id = "id",
data = reps2)
pr_test = print(nest_test)
p = plot(nest_test, type = 1)
p = plot(nest_test, type = 2)
#expect_warning(check(nest_test)$p_norm)
#expect_warning(check(nest_test)$p_het)
nest = reps2
nest_test2 = agree_nest(
x = "x",
y = "y",
delta = 2.5,
id = "id",
data = nest
)
nest_test3 = agree_nest(
x = "x",
y = "y",
delta = 2.5,
id = "id",
data = nest,
agree.level = .8,
conf.level = .75
)
nest_test4 = agree_nest(
x = "x",
y = "y",
delta = 2.5,
id = "id",
data = nest,
agree.level = .75,
conf.level = .8
)
pr_test = print(nest_test)
p = plot(nest_test, type = 1)
p = plot(nest_test, type = 2)
pr_test = print(nest_test2)
p = plot(nest_test2, type = 1)
p = plot(nest_test2, type = 2)
pr_test = print(nest_test3)
p = plot(nest_test3, type = 1)
p = plot(nest_test3, type = 2)
pr_test = print(nest_test3)
p = plot(nest_test3, type = 1)
p = plot(nest_test3, type = 1,
smooth_method = "lm")
p = plot(nest_test3, type = 1,
smooth_method = "loess")
expect_error(plot(nest_test3, type = 1,
smooth_method = "gam"))
p = plot(nest_test3, type = 1)
p = plot(nest_test3, type = 2)
test_jmv = jmvagreemulti(
data = nest,
method1 = "x",
method2 = "y",
id = "id"
)
#test_jmv$blandtab$asDF
#nest_test$loa
testthat::expect_equivalent(test_jmv$blandtab$asDF$estimate,
nest_test$loa$estimate)
testthat::expect_equivalent(test_jmv$blandtab$asDF$lowerci,
nest_test$loa$lower.ci)
testthat::expect_equivalent(test_jmv$blandtab$asDF$upperci,
nest_test$loa$upper.ci)
})
testthat::test_that("example from error message",{
set.seed(637234)
data2 = data.frame(IDNum = c(1,1,1,
2,2,
3,3,3,
4,4,4,
5,5,5,5,
6,6,
7,7,
8,8,
9,9,
10,10,10),
ACT_Sleep_Time = c(rnorm(3),
2,NA,
rnorm(3),
rnorm(3),
rnorm(4),
rnorm(2),
rnorm(2),
rnorm(2),
rnorm(2),
rnorm(3)),
E_TST1_minutes = c(rnorm(3),
rnorm(2),
rnorm(3),
rnorm(3),
rnorm(4),
rnorm(2),
rnorm(2),
rnorm(2),
-1,NA,
rnorm(3))
)
TSTnest = agree_nest(x = "ACT_Sleep_Time",
y = "E_TST1_minutes",
id = "IDNum",
#delta = 100,
data = data2,
agree.level = .8,
TOST = FALSE)
testthat::expect_equivalent(TSTnest$loa$estimate,
c(.597,-.568,1.761),
tolerance = 0.001)
testthat::expect_equivalent(TSTnest$loa$upper.ci,
c(1.0301,-0.0741,2.5673),
tolerance = 0.001)
testthat::expect_equivalent(TSTnest$loa$lower.ci,
c(.164,-1.373,1.268),
tolerance = 0.001)
TSTrep = agree_reps(x = "ACT_Sleep_Time",
y = "E_TST1_minutes",
id = "IDNum",
#delta = 100,
data = data2,
agree.level = .8,
TOST = FALSE)
testthat::expect_equivalent(TSTrep$loa$estimate,
c(.717,-.665,2.099),
tolerance = 0.001)
testthat::expect_equivalent(TSTrep$loa$upper.ci,
c(1.185,-.142,2.936),
tolerance = 0.001)
testthat::expect_equivalent(TSTrep$loa$lower.ci,
c(.249,-1.502,1.576),
tolerance = 0.001)
})
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