glm.weighted.dispersion

<p>The goal of this function is to estimate the glm dispersion parameter using data across imputed datasets while correctly accounting for the weights.</p>

Provides methods for inference using stacked multiple
imputations augmented with weights. The vignette provides example R code for
implementation in general multiple imputation settings. For additional details
about the estimation algorithm, we refer the reader to Beesley, Lauren J and
Taylor, Jeremy M G (2020) <e2><80><9c>A stacked approach for chained equations multiple
imputation incorporating the substantive model<e2><80><9d> <doi:10.1111/biom.13372>,
and Beesley, Lauren J and Taylor, Jeremy M G (2021) <e2><80><9c>Accounting for not-at-random
missingness through imputation stacking<e2><80><9d> <arXiv:2101.07954>.

Michael Kleinsasser

StackImpute

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glm.weighted.dispersion: glm.weighted.dispersion

Description

Usage

Arguments

Value

Examples