process_results {mmiCATs}R Documentation

Process Cluster-Adjusted Robust Inference Results

Description

This internal function processes results from cluster-specific model fittings for cluster-robust inference functions. It combines results, computes variance-covariance matrix, standard errors, t-statistics, p-values, and confidence intervals for each independent variable.

Usage

process_results(results, ind_variables, ci.level, drop, return.vcv)

Arguments

results

A list of results from cluster-specific model fittings.

ind_variables

A vector of independent variable names for which the results are computed.

ci.level

Confidence level for the confidence intervals.

drop

Logical; if TRUE, clusters with failed model fits are omitted from the results.

return.vcv

Logical; if TRUE, returns the variance-covariance matrix of the cluster-averaged coefficients.

Details

Workflow defined in clusterSEs::cluster.im.glm() function.

Value

A list containing the following elements:

p.values

A matrix of p-values for each independent variable.

ci

A matrix with the lower and upper bounds of the confidence intervals for each independent variable.

vcv.hat

The variance-covariance matrix of the cluster-averaged coefficients, returned if return.vcv is TRUE.

beta.bar

The cluster-averaged coefficients, returned if return.vcv is TRUE.


[Package mmiCATs version 0.1.1 Index]