bmem: Mediation analysis with missing data using bootstrap

Four methods for mediation analysis with missing data: Listwise deletion, Pairwise deletion, Multiple imputation, and Two Stage Maximum Likelihood algorithm. For MI and TS-ML, auxiliary variables can be included. Bootstrap confidence intervals for mediation effects are obtained. The robust method is also implemented for TS-ML. Since version 1.4, bmem adds the capability to conduct power analysis for mediation models.

AuthorZhiyong Zhang and Lijuan Wang
Date of publication2013-06-28 19:37:49
MaintainerZhiyong Zhang <zhiyongzhang@nd.edu>
LicenseGPL-2
Version1.4
http://psychstat.org

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Man pages

bmem: Mediation analysis based on bootstrap

bmem.bs: Bootstrap but using the Bollen-Stine method

bmem.ci.bc: Bias-corrected confidence intervals

bmem.ci.bc1: Bias-corrected confidence intervals (for a single variable)

bmem.ci.bca: Bias-corrected and accelerated confidence intervals

bmem.ci.bca1: BCa for a single variable

bmem.ci.norm: Confidence interval based on normal approximation

bmem.ci.p: Percentile confidence interval

bmem.cov: Calculate the covariance matrix based on a given ram model

bmem.em: Estimate a mediation model based on EM covariance matrix

bmem.em.boot: Bootstrap for EM

bmem.em.cov: Covariance matrix from EM

bmem.em.jack: Jackknife estimate using EM

bmem.em.rcov: Estimation of robust covariance matrix

bmem.list: Estimate a mediaiton model based on listwise deletion

bmem.list.boot: Bootstrap for listwise deletion method

bmem.list.cov: Covariance matrix for listwise deletion

bmem.list.jack: Jackknife for listwise deletion

bmem.mi: Estimate a mediation model based on multiple imputation

bmem.mi.boot: Bootstrap for multiple imputation

bmem.mi.cov: Covariance estimation for multiple imputation

bmem.mi.jack: Jackknife for multiple imputation

bmem.moments: Calculate the moments of a data set

bmem-package: Mediation analysis with missing data using bootstrap

bmem.pair: Estimate a mediaiton model based on pairwise deletion

bmem.pair.boot: Bootstrap for pairwise deletion

bmem.pair.cov: Covariance matrix estimation based on pairwise deletion

bmem.pair.jack: Jackknife for pairwise deletion

bmem.pattern: Obtain missing data pattern information

bmem.plot: Plot of the bootstrap distribution. This function is replaced...

bmem.raw2cov: Convert a raw moment matrix to covariance matrix

bmem.sem: Estimate a mediaiton model using SEM technique

bmem.sobel: Mediation analysis using sobel test (for complete data only)

bmem.sobel.ind: Mediation analysis using sobel test for one indirect effect

bmem.ssq: Sum square of a matrix

bmem.v: Select data according to a vector of indices

plot.bmem: Plot of the bootstrap distribution

popPar: Get the population parameter values

power.basic: Conducting power analysis based on Sobel test

power.boot: Conducting power analysis based on bootstrap

power.curve: Generate a power curve

summary.bmem: Calculate bootstrap confidence intervals

summary.power: Organize the results into a table

Questions? Problems? Suggestions? or email at ian@mutexlabs.com.

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