wqs.pool.test: Combining WQS Regression Estimates

In miWQS: Multiple Imputation Using Weighted Quantile Sum Regression

Description

wqs.pool.test was produced to demonstrate pool.mi(). First, the univariate Bayesian imputation approach (using impute.univariate.bayesian.mi) imputed the X.bdl element of simdata87 multiple times to form an imputed X array. Multiple WQS regressions were run on the imputed X array to produce an array of WQS parameter estimates, wqs.pool.test.

Usage

data(wqs.pool.test)

Format

An array of 16 x 2 x 3, with

• 16 parameters as the rows (The 14 weights, intercept, and WQS estimate of a WQS model),

• 2 refers to the parameters of mean and standard deviation

• K=3 complete imputed datasets.

See Also

pool.mi

Examples

wqs.pool.test <- data(wqs.pool.test)
# stage_3_pool_mi_example

Example output

miWQS documentation built on April 3, 2021, 1:06 a.m.