mice.impute.lag: Compute Lagging Values of an Imputed Response

In santikka/dynamite: Bayesian Modeling and Causal Inference for Multivariate Longitudinal Data

Compute Lagging Values of an Imputed Response

Description

Function for computing the lagged values of an imputed response in mice.

Usage

mice.impute.lag(y, ry, x, wy = NULL, group_val, group_var, resp, ...)

Arguments

y	Vector to be imputed
ry	Logical vector of length length(y) indicating the the subset y[ry] of elements in y to which the imputation model is fitted. The ry generally distinguishes the observed (TRUE) and missing values (FALSE) in y.
x	Numeric design matrix with length(y) rows with predictors for y. Matrix x may have no missing values.
wy	Logical vector of length length(y). A TRUE value indicates locations in y for which imputations are created.
group_val	[vector()] Values of the grouping variable.
group_var	[character(1)] Name of the grouping variable.
resp	[character(1)] Name of the response variable.
...	Other named arguments.

santikka/dynamite documentation built on April 17, 2025, 11:47 a.m.