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metaSEM (version 0.9.8)

Meta-Analysis using Structural Equation Modeling

Description

A collection of functions for conducting meta-analysis using a structural equation modeling (SEM) approach via the 'OpenMx' package. It also implements the two-stage SEM approach to conduct meta-analytic structural equation modeling on correlation and covariance matrices.

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Install

install.packages('metaSEM')

Monthly Downloads

820

Version

0.9.8

License

GPL (>= 2)

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Repository

https://github.com/mikewlcheung/metasem

Maintainer

Mike Cheung

Last Published

April 19th, 2016

Functions in metaSEM (0.9.8)

Estimate Variance Components with Restricted (Residual) Maximum Likelihood Estimation

metaSEM-package

Meta-Analysis using Structural Equation Modeling

Selected effect sizes from Cooper et al. (2003)

Create a Block Diagonal Matrix

Create an F matrix to select observed variables

Matrix Diagonals

Studies on Students' School Engagement and Achievement Reported by Roorda et al. (2011)

Convert lavaan models to RAM models

Display the Pattern of Missing Data of a List of Square Matrices

Estimate Variance Components in Three-Level Univariate Meta-Analysis with Restricted (Residual) Maximum Likelihood Estimation

Conduct a Correlation/Covariance Structure Analysis with WLS

Display the Accumulative Sample Sizes for the Covariance Matrix

Convert a Matrix into a Block Diagonal Matrix

Dataset on the Effectiveness of the BCG Vaccine for Preventing Tuberculosis

Print Methods for tssem1FEM, tssem1FEM.cluster, tssem1REM, wls, meta, meta3X and reml Objects

First Stage of the Two-Stage Structural Equation Modeling (TSSEM)

Forty-four Studies from Cheung (2013)

Five Published Trails from Berkey et al. (1998)

Six Studies of Correlation Matrices reported by Becker (1992; 1995)

Eight studies from Mak et al. (2009)

Simulated Effect Sizes Reported by Hox (2002)

Fourteen Studies of Correlation Matrices reported by Hunter (1983)

Convert a Vector into a Symmetric Matrix

Test Positive Definiteness of a List of Square Matrices

create.mxMatrix

Create a Vector into MxMatrix-class

Data Set from ISSP (2005)

Three-Level Univariate Meta-Analysis with Maximum Likelihood Estimation

Plot method for meta objects

Rerun models via mxTryHard()

Effects of Open Education Reported by Hedges and Olkin (1985)

Five Studies of Ten Correlation Matrices reported by Becker and Schram (1994)

Fifty Studies of Correlation Matrices used in Cheung and Chan (2000)

Convert metaSEM objects into semPlotModel objects for plotting

Studies on Sex Differences in Conformity Reported by Becker (1983)

Compute Asymptotic Covariance Matrix of a Correlation/Covariance Matrix

Ten Studies of Correlation Matrices used by Becker (2009)

Create a Block Diagonal Matrix by Repeating the Input

Compare Nested Models with Likelihood Ratio Statistic

Convert a Matrix into MxMatrix-class

Extract Covariance Matrix Parameter Estimates from Various Objects

Forty-four Covariance Matrices on Life Satisfaction, Job Satisfaction, and Job Autonomy

Test the Homogeneity of Effect Sizes

Data Set from Cheung and Chan (2005; 2009)

Univariate and Multivariate Meta-Analysis with Maximum Likelihood Estimation

Extract Parameter Estimates from tssem1FEM, tssem1FEM.cluster, tssem1REM, wls, wls.cluster, meta, meta3X, reml and MxRAMModel Objects

Summary Method for tssem1, wls, meta and meta3X Objects

A Data Set from TSSEM User's Guide Version 1.11 by Cheung (2009)

Multivariate effect sizes between classroom management self-efficacy (CMSE) and other variables reported by Aloe et al. (2014)

Estimate the asymptotic covariance matrix of standardized or unstandardized indirect and direct effects

Studies on the Hospital Anxiety and Depression Scale Reported by Norton et al. (2013)

Convert a List of Symmetric Matrices into a Stacked Matrix

A Dataset from Bornmann et al. (2007)

Read External Correlation/Covariance Matrices

Dataset from Jaramillo, Mulki & Marshall (2005)

Factor Correlation Matrices of Big Five Model from Digman (1997)