Nothing
library(nlme, quietly = TRUE)
data(Socatt, package = "mlmRev")
Socatt$religion <- relevel(Socatt$religion, ref = "none")
Socatt$rv <- as.numeric(as.character(Socatt$numpos))
Socatt$rv <- scale(Socatt$rv) # a plot shows this is clearly non-normal
# ==============================================================================
context("case bootstrap (lme)")
# ==============================================================================
mySumm <- function(.) {
c(beta = fixef(.), sigma = as.numeric(.$sigma), sig01 = as.numeric(VarCorr(.)[1,2]))
}
nsim <- 10
test_that("two-level additive random intercept model",{
skip_on_cran()
## See p. 31 of Goldstein's book
vcmodA <- lme(mathAge11 ~ mathAge8 + gender + class,
random = ~ 1 | school, data = jsp728)
orig.stats <- mySumm(vcmodA)
boo <- case_bootstrap(model = vcmodA, .f = mySumm, B = nsim, resample = c(TRUE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
boo <- case_bootstrap(model = vcmodA, .f = mySumm, B = nsim, resample = c(FALSE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
boo <- case_bootstrap(model = vcmodA, .f = mySumm, B = nsim, resample = c(TRUE, FALSE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
})
# ------------------------------------------------------------------------------
test_that("two-level random intercept model with interaction",{
skip_on_cran()
## See p. 34 of Goldstein's book
vcmodC <- lme(mathAge11 ~ mathAge8 * schoolMathAge8 + gender + class,
random = ~ 1 | school, data = jsp728)
orig.stats <- mySumm(vcmodC)
boo <- case_bootstrap(model = vcmodC, .f = mySumm, B = nsim, resample = c(TRUE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
boo <- case_bootstrap(model = vcmodC, .f = mySumm, B = nsim, resample = c(FALSE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
})
# ------------------------------------------------------------------------------
test_that("two-level random coefficient model with interaction",{
skip_on_cran()
## See p. 35 of Goldstein's book
rcmod <- lme(mathAge11 ~ mathAge8c * schoolMathAge8 + gender + class,
random = ~ mathAge8c | school, data = jsp728)
orig.stats <- mySumm(rcmod)
boo <- case_bootstrap(model = rcmod, .f = mySumm, B = nsim, resample = c(TRUE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
})
# ------------------------------------------------------------------------------
test_that("three-level random coefficient model with interaction",{
skip_on_cran()
rmA <- lme(rv ~ religion + year, random = ~ 1 | district/respond, data = Socatt)
mySumm <- function(.) {
c(beta = fixef(.), sigma = as.numeric(.$sigma),
sig.dist = as.numeric(VarCorr(.)[2,2]),
sig.int = as.numeric(VarCorr(.)[4,2]))
}
orig.stats <- mySumm(rmA)
boo <- case_bootstrap(model = rmA, .f = mySumm, B = nsim,
resample = c(TRUE, TRUE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
boo <- case_bootstrap(model = rmA, .f = mySumm, B = nsim,
resample = c(FALSE, FALSE, TRUE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
boo <- case_bootstrap(model = rmA, .f = mySumm, B = nsim,
resample = c(TRUE, TRUE, FALSE))
expect_equal(class(boo), "lmeresamp")
expect_equal(boo$observed, orig.stats)
expect_equal(unname(boo$stats$observed), unname(orig.stats))
expect_equal(nrow(boo$replicates), nsim)
expect_equal(ncol(boo$replicates), length(orig.stats))
expect_equal(boo$B, nsim)
expect_equal(boo$type, "case")
expect_equal(boo$.f, mySumm)
})
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