lme_permute2 {crctStepdown}R Documentation

Generate a new permutation

Description

Returns the test statistic from a specified null hypothesis and model under a single new permutation

Usage

lme_permute2(
  fitlist,
  data,
  null_par = rep(0, length(fitlist)),
  cl_var = "cl",
  rand_func = NULL
)

Arguments

fitlist

A list of glm model objects fitted under the null hypotheses

data

A data frame containing the data used to fit the models in fitlist

null_par

A vector of the same length as fitlist specifying the value(s) of the treatment effect parameter(s) under the null hypotheses

cl_var

String specifying the name of the column identifying the clusters/cluster-time

rand_func

String of the name of a function that re-randomises the clusters. The function should produce a data frame that identifies the clusters in the treatment group under the new randomisation scheme. The data frame can either have a single column with name cl_var or two columns of cl_var and t identifying the cluster ID and time period a cluster joins the treatment group. If NULL then clusters are randomised in a 1:1 ratio to treatment and control

Value

A vector of the length of fitlist with the test statistics for each model and null hypothesis

Examples

out <- twoarm_sim()
data <- out[[1]]
  fit1 <- lme4::glmer(y1 ~ treat + (1|cl) ,
data=data,
family="poisson")

fit2 <- lme4::glmer(y2 ~ treat + (1|cl),
                    data=data,
                    family="poisson")
fitlist <- list(fit1,fit2)
nullfitlist <- list()
for(i in 1:length(fitlist)){
  nullfitlist[[i]] <- est_null_model(fitlist[[i]],
                                     data,
                                     tr_var = "treat",
                                     null_par = 0)
}
out <- lme_permute2(nullfitlist,
               data=data,
               cl_var = "cl")

[Package crctStepdown version 0.2.1 Index]