About Anaconda Help Download Anaconda

We implement causal mediation analysis using the methods proposed by Hong (2010) and Hong, Deutsch & Hill (2015) <doi:10.3102/1076998615583902>. It allows the estimation and hypothesis testing of causal mediation effects through ratio of mediator probability weights (RMPW). This strategy conveniently relaxes the assumption of no treatment-by-mediator interaction while greatly simplifying the outcome model specification without invoking strong distributional assumptions. We also implement a sensitivity analysis by extending the RMPW method to assess potential bias in the presence of omitted pretreatment or posttreatment covariates. The sensitivity analysis strategy was proposed by Hong, Qin, and Yang (2018) <doi:10.3102/1076998617749561>.

Click on a badge to see how to embed it in your web page
badge
https://anaconda.org/r/r-rmpw/badges/version.svg
badge
https://anaconda.org/r/r-rmpw/badges/latest_release_date.svg
badge
https://anaconda.org/r/r-rmpw/badges/latest_release_relative_date.svg
badge
https://anaconda.org/r/r-rmpw/badges/platforms.svg
badge
https://anaconda.org/r/r-rmpw/badges/license.svg
badge
https://anaconda.org/r/r-rmpw/badges/downloads.svg

© 2024 Anaconda, Inc. All Rights Reserved. (v4.0.5) Legal | Privacy Policy