recursive.test: Recursive Multivariate Testing

In yqzhong7/relate: REcursive muLtivariAte TEsting for cohort clustering

Recursive Multivariate Testing

Description

This recursion function conducts the Biswas and Ghosh multivariate test based on the dendrogram from the hierarchical clustering of the average distance matrix of the unsupervised random forest.

Usage

recursive.test(
  dend,
  df,
  cateVar = NULL,
  ordinalVar = NULL,
  cohortid.var = "cohortid",
  alpha.level = 0.05,
  verbose = T,
  saveIntermediate = F,
  BG.method = "asymptotic",
  n_perm = 200,
  N_auto = 50,
  impute = T,
  miceArgs = list(method = "mean", maxit = 1)
)

Arguments

dend	dendrogram object from the stat::as.as.dendrogram()
df	data.frame
cateVar	string or vector, names of variables are categorical, which will be converted into dummy variables
ordinalVar	string or vector, names of variables are ordinal factors, which will be converted into numeric variables
cohortid.var	string, name of the cohort id indicator in the relate::df
alpha.level	numeric, alpha level for statistical significance of the BG test
verbose	boolean, whether to print the intermediate test results at each round
saveIntermediate	boolean, whether to save the intermediate test result in the final output
BG.method	string, "asymptotic","permutation","automatic", see relate::BGcompare above
n_perm	number of permutation if method is permutation
N_auto	integer, the sample size for automatically choosing between asymptotic and permutation, below is permutation, above is asymptotic
impute	boolean, whether to conduct MICE imputation within clusters before testing
miceArgs	list, a list of arguments parse into mice::mice

yqzhong7/relate documentation built on Jan. 29, 2023, 6:33 p.m.