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mzipmed (version 1.4.0)

Mediation using MZIP Model

Description

We implement functions allowing for mediation analysis to be performed in cases where the mediator is a count variable with excess zeroes. First a function is provided allowing users to perform analysis for zero-inflated count variables using the marginalized zero-inflated Poisson (MZIP) model (Long et al. 2014 ). Using the counterfactual approach to mediation and MZIP we can obtain natural direct and indirect effects for the overall population. Using delta method processes variance estimation can be performed instantaneously. Alternatively, bootstrap standard errors can be used. We also provide functions for cases with exposure-mediator interactions with four-way decomposition of total effect.

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Version

Install

install.packages('mzipmed')

Monthly Downloads

238

Version

1.4.0

License

MIT + file LICENSE

Maintainer

Andrew Sims

Last Published

July 7th, 2023

Functions in mzipmed (1.4.0)

binoutzimedint

Mediation Analysis for Zero-Inflated Count Mediators using MZIP with Exposure-Mediator Interactions (Binary/Count Outcome)
binoutzimed

Mediation Analysis for Zero-Inflated Count Mediators using MZIP (Binary or Count Outcome)
mzipmed_data

Data to be used in the mzipmed package examples
zioutlmmedint

Mediation Analysis for Zero-Inflated Count Outcomes using MZIP with Exposure-Mediator Interactions
zioutlmmed

Mediation Analysis for Zero-Inflated Count Outcomes using MZIP
lmoutzimed

Mediation Analysis for Zero-Inflated Count Mediators using MZIP (Continuous Outcome)
zioutbinmedint

Mediation Analysis for Zero-Inflated Count Outcomes using MZIP with Exposure-Mediator Interactions (Binary Outcome)
zioutbinmed

Mediation Analysis for Zero-Inflated Count Outcomes using MZIP with binary mediators
mzip

Marginalized Zero-Inflated Poisson Regression Model
lmoutzimedint

Mediation Analysis for Zero-Inflated Count Mediators using MZIP with Exposure-Mediator Interactions (Continuous Outcome)