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 <>

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Man pages

bmem: Mediation analysis based on bootstrap Bootstrap but using the Bollen-Stine method Bias-corrected confidence intervals Bias-corrected confidence intervals (for a single variable) Bias-corrected and accelerated confidence intervals BCa for a single variable Confidence interval based on normal approximation 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


bmem Man page Man page Man page Man page Man page Man page Man page Man page
bmem.cov Man page
bmem.em Man page
bmem.em.boot Man page
bmem.em.cov Man page
bmem.em.jack Man page
bmem.em.rcov Man page
bmem.list Man page
bmem.list.boot Man page
bmem.list.cov Man page
bmem.list.jack Man page
bmem.mi Man page
bmem.mi.boot Man page
bmem.mi.cov Man page
bmem.mi.jack Man page
bmem.moments Man page
bmem-package Man page
bmem.pair Man page
bmem.pair.boot Man page
bmem.pair.cov Man page
bmem.pair.jack Man page
bmem.pattern Man page
bmem.plot Man page
bmem.raw2cov Man page
bmem.sem Man page
bmem.sobel Man page
bmem.sobel.ind Man page
bmem.ssq Man page
bmem.v Man page
plot Man page
plot.bmem Man page
popPar Man page
power.basic Man page
power.boot Man page
power.curve Man page
summary Man page
summary.bmem Man page
summary.power Man page

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