mice_nonign_temp: Non-ingorably MI for difference in proportions via MICE

In yuliasidi/nibinom:

Description

two-stage MI for difference in proportions using MICE

Usage

mice_nonign_temp(dt, n_mi = 5, m_mi = 10, m2, ci_method = ci_method,
  seed_mice, mu_C = 1, sd_C = 0, mu_T = 1, sd_T = 0)

Arguments

dt	dataframe
n_mi	numeric, number of patient level imputations, Default: 5
m_mi	numeric, number of model imputations, Default: 10
m2	numeric, margin
ci_method	ci function name, Default: ci_method
seed_mice	numeric
mu_C	numeric, mean parameter for k multiplier normal distribution for group 'c', Default: 1
sd_C	numeric, stadnard deviation parameter for k multiplier normal distribution for group 'c', Default: 0
mu_T	Pnumeric, mean parameter for k multiplier normal distribution for group 't',Default: 1
sd_T	numeric, stadnard deviation parameter for k multiplier normal distribution for group 't', Default: 0

Value

final result following nested multiple imputation

See Also

make.predictorMatrix,mice get_env tibble map,map2 Uniform,Normal unnest,nest

yuliasidi/nibinom documentation built on Dec. 14, 2021, 11:43 p.m.