Package: sensmediation 0.3.0

sensmediation: Parametric Estimation and Sensitivity Analysis of Direct and Indirect Effects

We implement functions to estimate and perform sensitivity analysis to unobserved confounding of direct and indirect effects introduced in Lindmark, de Luna and Eriksson (2018) <doi:10.1002/sim.7620>. The estimation and sensitivity analysis are parametric, based on probit and/or linear regression models. Sensitivity analysis is implemented for unobserved confounding of the exposure-mediator, mediator-outcome and exposure-outcome relationships.

Authors:Anita Lindmark <[email protected]>

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sensmediation.pdf |sensmediation.html✨
sensmediation/json (API)
NEWS

# Install 'sensmediation' in R:
install.packages('sensmediation', repos = c('https://anitalindmark.r-universe.dev', 'https://cloud.r-project.org'))

Peer review:

Datasets:
  • RSdata - Example data for the functions in sensmediation

On CRAN:

This package does not link to any Github/Gitlab/R-forge repository. No issue tracker or development information is available.

32 exports 0.36 score 8 dependencies 1 mentions 4 scripts 141 downloads

Last updated 5 years agofrom:d4922a7804. Checks:OK: 5 NOTE: 2. Indexed: yes.

TargetResultDate
Doc / VignettesOKSep 10 2024
R-4.5-winNOTESep 10 2024
R-4.5-linuxNOTESep 10 2024
R-4.4-winOKSep 10 2024
R-4.4-macOKSep 10 2024
R-4.3-winOKSep 10 2024
R-4.3-macOKSep 10 2024

Exports:calc.effectscoefs.sensmedeff.bbeff.bceff.cbeff.ccgrr.bbgrr.bcgrr.cbgrr.cchess.bbhess.bchess.cbhess.ccLogL.bbLogL.bcLogL.cbLogL.ccML.bbML.bcML.cbML.ccmore.effectspartdevs.bbpartdevs.bcpartdevs.cbpartdevs.ccsensmediationstderr.bbstderr.bcstderr.cbstderr.cc

Dependencies:digestgenericslatticemaxLikmiscToolsmvtnormsandwichzoo

Readme and manuals

Help Manual

Help pageTopics
Function for estimation of natural direct and indirect effects and sensitivity analysis for unobserved mediator-outcome confoundingcalc.effects
ML estimation of regression parameters for calculation of direct and indirect effects under unobserved confoundingcoefs.sensmed
Functions to calculate natural direct and indirect effects.eff.bb eff.bc eff.cb eff.cc effects
Analytic gradients of the loglikelihood functions for ML estimation of regression parametersgrr grr.bb grr.bc grr.cb grr.cc
Analytic Hessians of the loglikelihood functions for ML estimation of regression parametershess hess.bb hess.bc hess.cb hess.cc
Implementation of loglikelihood functions for ML estimation of regression parametersLogL LogL.bb LogL.bc LogL.cb LogL.cc
Functions for ML estimation of regression parameters for sensitivity analysisML ML.bb ML.bc ML.cb ML.cc
Estimate additional natural direct and indirect effects based on an '"effectsMed"' objectmore.effects
Implementations of the partial derivatives (gradients) of the expressions for the direct, indirect and total effects. Used to calculate standard errors (delta method).partdevs partdevs.bb partdevs.bc partdevs.cb partdevs.cc
Plot function for objects of class '"effectsMed"'plot.effectsMed
Example data for the functions in sensmediationRSdata
Estimate natural direct and indirect effects based on parametric regression models and perform sensitivity analysissensmediation
Functions to calculate standard errors of the direct, indirect and total effects using the delta method.stderr.bb stderr.bc stderr.cb stderr.cc stderrs
Summary function for objects of class '"effectsMed"'print.summaryeffectsMed summary.effectsMed