inputcheck: Input checker

In matthiasspeidel/hmi: Hierarchical Multiple Imputation

Description

A help function to check whether in input is correct.

Usage

inputcheck(data, model_formula, y, X, Z, cl.id, n.iter, M, n.chains, burn.in)

Arguments

data	A matrix or (better) a data.frame with all variables appearing in model_formula.
model_formula	A formula used for the analysis model.
y	A vector or data.frame with ncol = 1 containing the target variable with the missing values.
X	A vector a data.frame containing the covariates influencing y via fixed effects. If rows with missing values in X should also be imputed, put all your variables in a data.frame (or matrix)
Z	A vector a data.frame containing the covariates influencing y via random effects
cl.id	A factor (should come as data.frame or vector) containing the cluster IDs.
n.iter	An integer defining the number of iterations that should be run in each bunch of iterations.
M	An integer defining the number of imputations that should be made.
n.chains	An integer defining the number of Markov chains to be made.
burn.in	A numeric between 0 and 1 defining the percentage of draws from the gibbs sampler that should be discarded as burn in.

Value

Nothing. In some cases prompts might be cast.

matthiasspeidel/hmi documentation built on Aug. 18, 2020, 4:37 p.m.