MFClusBootHier: MFClusBootHier

In ABS-dev/MF: Mitigated Fraction

MFClusBootHier

Description

Combines MFhBoot and MFnestBoot into a single function.

Usage

MFClusBootHier(
  formula,
  data,
  compare = c("con", "vac"),
  nboot = 10000,
  boot.unit = TRUE,
  boot.cluster = TRUE,
  which.factor = "All",
  alpha = 0.05,
  seed = sample(1:1e+05, 1)
)

Arguments

formula	formula Formula of the form y ~ x + a/b/c, where y is a continuous response, x is a factor with two levels of treatment, and a/b/c are grouping variables corresponding to the clusters. Nesting is assumed to be in order, left to right, highest to lowest. So a single level of "a" will contain multiple levels of "b" and a single level of "b" will contain multiple levels of "c".
data	a data.frame or tibble with the variables specified in formula. Additional variables will be ignored.
compare	Text vector stating the factor levels - compare[1] is the control or reference group to which compare[2] is compared.
nboot	number of bootstrapping events
boot.unit	Boolean whether to sample observations from within those of the same core.
boot.cluster	Boolean whether to sample which cores are present. If TRUE, some trees have all the cores while others only have a subset.
which.factor	Which variables to include in the mitigated fraction summation. Default is 'All', to sum over entire tree.
alpha	Passed to emp_hpd to calculate high tailed upper and high tailed lower of mitigated fraction.
seed	Passed to MFhBoot to to initialize random number generator for reproducibility.

Value

A list with the following elements:

• MFhBoot as output from MFhBoot.

• MFnestBoot as output from MFnestBoot.

Note

Core variable is the variable corresponding to the lowest nodes of the hierarchical tree. Nest variables are those above the core. All refers to a summary of the entire tree.

Author(s)

MF-package

See Also

MFhBoot, MFnestBoot.

Examples

a <- data.frame(
  room = paste('Room', rep(c('W','Z'), each=24)),
  pen = paste('Pen', rep(LETTERS[1:6], each=8)),
  litter = paste('Litter', rep(11:22, each=4)),
  tx = rep(rep(c('vac','con'), each=2), 12),
  stringsAsFactors = FALSE
)
set.seed(76153)
a$lung[a$tx=='vac'] <- rnorm(24, 5, 1.3)
a$lung[a$tx=='con'] <- rnorm(24, 7, 1.3)
thismf1 <- MFClusBootHier(lung ~ tx + room / pen / litter, a, nboot = 10000,
                       boot.cluster = TRUE, boot.unit = TRUE, seed = 12345)
thismf1

ABS-dev/MF documentation built on April 21, 2024, 5:55 p.m.