A B C D G H I J K L M N O P R S T U V W
metaSEM-package | Meta-Analysis using Structural Equation Modeling |
Aloe14 | Multivariate effect sizes between classroom management self-efficacy (CMSE) and other variables reported by Aloe et al. (2014) |
anova.meta | Compare Nested Models with Likelihood Ratio Statistic |
anova.meta3LFIML | Compare Nested Models with Likelihood Ratio Statistic |
anova.mxRAMmodel | Compare Nested Models with Likelihood Ratio Statistic |
anova.osmasem | Compare Nested Models with Likelihood Ratio Statistic |
anova.reml | Compare Nested Models with Likelihood Ratio Statistic |
anova.wls | Compare Nested Models with Likelihood Ratio Statistic |
as.mxAlgebra | Convert a Character Matrix into MxAlgebra-class |
as.mxMatrix | Convert a Matrix into MxMatrix-class |
as.symMatrix | Convert a Character Matrix with Starting Values to a Character Matrix without Starting Values |
asyCov | Compute Asymptotic Covariance Matrix of a Correlation/Covariance Matrix |
asyCovOld | Compute Asymptotic Covariance Matrix of a Correlation/Covariance Matrix |
BCG | Dataset on the Effectiveness of the BCG Vaccine for Preventing Tuberculosis |
bdiagMat | Create a Block Diagonal Matrix |
bdiagRep | Create a Block Diagonal Matrix by Repeating the Input |
Becker09 | Ten Studies of Correlation Matrices used by Becker (2009) |
Becker83 | Studies on Sex Differences in Conformity Reported by Becker (1983) |
Becker92 | Six Studies of Correlation Matrices reported by Becker (1992; 1995) |
Becker94 | Five Studies of Ten Correlation Matrices reported by Becker and Schram (1994) |
Berkey98 | Five Published Trails from Berkey et al. (1998) |
Boer16 | Correlation Matrices from Boer et al. (2016) |
bootuniR1 | Parametric bootstrap on the univariate R (uniR) object |
bootuniR2 | Fit Models on the bootstrapped correlation matrices |
Bornmann07 | A Dataset from Bornmann et al. (2007) |
calEffSizes | Calculate Effect Sizes using lavaan Models |
checkRAM | Check the correctness of the RAM formulation |
Cheung00 | Fifty Studies of Correlation Matrices used in Cheung and Chan (2000) |
Cheung09 | A Dataset from TSSEM User's Guide Version 1.11 by Cheung (2009) |
coef.meta | Extract Parameter Estimates from various classes. |
coef.meta3LFIML | Extract Parameter Estimates from various classes. |
coef.mxRAMmodel | Extract Parameter Estimates from various classes. |
coef.osmasem | Extract Parameter Estimates from various classes. |
coef.reml | Extract Parameter Estimates from various classes. |
coef.tssem1FEM | Extract Parameter Estimates from various classes. |
coef.tssem1FEM.cluster | Extract Parameter Estimates from various classes. |
coef.tssem1REM | Extract Parameter Estimates from various classes. |
coef.wls | Extract Parameter Estimates from various classes. |
coef.wls.cluster | Extract Parameter Estimates from various classes. |
Cooke16 | Correlation Matrices from Cooke et al. (2016) |
Cooper03 | Selected effect sizes from Cooper et al. (2003) |
Cor2DataFrame | Convert correlation or covariance matrices into a dataframe of correlations or covariances with their sampling covariance matrices |
create.Fmatrix | Create an F matrix to select observed variables |
create.modMatrix | Create a moderator matrix used in OSMASEM |
create.mxMatrix | Create a Vector into MxMatrix-class |
create.mxModel | Create an mxModel |
create.Tau2 | Create a variance component of the heterogeneity of the random effects |
create.V | Create a V-known matrix |
create.vechsR | Create a model implied correlation matrix with implicit diagonal constraints |
Diag | Matrix Diagonals |
Diag<- | Matrix Diagonals |
Digman97 | Factor Correlation Matrices of Big Five Model from Digman (1997) |
Gleser94 | Two Datasets from Gleser and Olkin (1994) |
Gnambs18 | Correlation Matrices from Gnambs, Scharl, and Schroeders (2018) |
HedgesOlkin85 | Effects of Open Education Reported by Hedges and Olkin (1985) |
homoStat | Test the Homogeneity of Effect Sizes |
Hox02 | Simulated Effect Sizes Reported by Hox (2002) |
Hunter83 | Fourteen Studies of Correlation Matrices reported by Hunter (1983) |
impliedR | Create or Generate the Model Implied Correlation or Covariance Matrices |
indirectEffect | Estimate the asymptotic covariance matrix of standardized or unstandardized indirect and direct effects |
is.pd | Test Positive Definiteness of a List of Square Matrices |
issp05 | A Dataset from ISSP (2005) |
issp89 | A Dataset from Cheung and Chan (2005; 2009) |
Jaramillo05 | Dataset from Jaramillo, Mulki & Marshall (2005) |
Kalaian96 | Multivariate effect sizes reported by Kalaian and Raudenbush (1996) |
lavaan2RAM | Convert 'lavaan' models to RAM models |
list2matrix | Convert a List of Symmetric Matrices into a Stacked Matrix |
Mak09 | Eight studies from Mak et al. (2009) |
Mathieu15 | Correlation Matrices from Mathieu et al. (2015) |
matrix2bdiag | Convert a Matrix into a Block Diagonal Matrix |
meta | Univariate and Multivariate Meta-Analysis with Maximum Likelihood Estimation |
meta2semPlot | Convert 'metaSEM' objects into 'semPlotModel' objects for plotting |
meta3 | Three-Level Univariate Meta-Analysis with Maximum Likelihood Estimation |
meta3L | Three-Level Univariate Meta-Analysis with Maximum Likelihood Estimation |
meta3LFIML | Three-Level Univariate Meta-Analysis with Maximum Likelihood Estimation |
meta3X | Three-Level Univariate Meta-Analysis with Maximum Likelihood Estimation |
metaFIML | Univariate and Multivariate Meta-Analysis with Maximum Likelihood Estimation |
metaSEM | Meta-Analysis using Structural Equation Modeling |
Nam03 | Dataset on the Environmental Tobacco Smoke (ETS) on children's health |
Nohe15A1 | Correlation Matrices from Nohe et al. (2015) |
Nohe15A2 | Correlation Matrices from Nohe et al. (2015) |
Norton13 | Studies on the Hospital Anxiety and Depression Scale Reported by Norton et al. (2013) |
osmasem | One-stage meta-analytic structural equation modeling |
osmasemR2 | Calculate the R2 in OSMASEM and OSMASEM3L |
osmasemSRMR | Calculate the SRMR in OSMASEM and OSMASEM3L |
pattern.n | Display the Accumulative Sample Sizes for the Covariance Matrix |
pattern.na | Display the Pattern of Missing Data of a List of Square Matrices |
plot.character | Plot methods for various objects |
plot.meta | Plot methods for various objects |
plot.mxRAMmodel | Plot methods for various objects |
plot.osmasem | Plot methods for various objects |
plot.wls | Plot methods for various objects |
print.impliedR | Print Methods for various Objects |
print.meta | Print Methods for various Objects |
print.meta3LFIML | Print Methods for various Objects |
print.reml | Print Methods for various Objects |
print.summary.bootuniR2 | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.Cor3L | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.CorPop | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.meta | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.meta3LFIML | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.mxRAMmodel | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.reml | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.tssem1FEM | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.tssem1FEM.cluster | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.summary.wls | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
print.tssem1FEM | Print Methods for various Objects |
print.tssem1FEM.cluster | Print Methods for various Objects |
print.tssem1REM | Print Methods for various Objects |
print.uniR1 | Print Methods for various Objects |
print.wls | Print Methods for various Objects |
rCor | Generate (Nested) Sample/Population Correlation/Covariance Matrices |
rCor3L | Generate (Nested) Sample/Population Correlation/Covariance Matrices |
rCorPop | Generate (Nested) Sample/Population Correlation/Covariance Matrices |
rCorSam | Generate (Nested) Sample/Population Correlation/Covariance Matrices |
readFullMat | Read External Correlation/Covariance Matrices |
readLowTriMat | Read External Correlation/Covariance Matrices |
readStackVec | Read External Correlation/Covariance Matrices |
reml | Estimate Variance Components with Restricted (Residual) Maximum Likelihood Estimation |
reml3 | Estimate Variance Components in Three-Level Univariate Meta-Analysis with Restricted (Residual) Maximum Likelihood Estimation |
reml3L | Estimate Variance Components in Three-Level Univariate Meta-Analysis with Restricted (Residual) Maximum Likelihood Estimation |
rerun | Rerun models via mxTryHard() |
rimpliedR | Create or Generate the Model Implied Correlation or Covariance Matrices |
Roorda11 | Studies on Students' School Engagement and Achievement Reported by Roorda et al. (2011) |
Scalco17 | Correlation Matrices from Scalco et al. (2017) |
smdMES | Compute Effect Sizes for Multiple End-point Studies |
smdMTS | Compute Effect Sizes for Multiple Treatment Studies |
Stadler15 | Correlations from Stadler et al. (2015) |
summary.bootuniR2 | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.Cor3L | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.CorPop | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.meta | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.meta3LFIML | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.mxRAMmodel | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.osmasem | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.reml | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.tssem1FEM | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.tssem1FEM.cluster | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.tssem1REM | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.wls | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
summary.wls.cluster | Summary Method for tssem1, wls, meta, and meta3LFIML Objects |
Tenenbaum02 | Correlation coefficients reported by Tenenbaum and Leaper (2002) |
tssem1 | First Stage of the Two-Stage Structural Equation Modeling (TSSEM) |
tssem1FEM | First Stage of the Two-Stage Structural Equation Modeling (TSSEM) |
tssem1REM | First Stage of the Two-Stage Structural Equation Modeling (TSSEM) |
tssem2 | Conduct a Correlation/Covariance Structure Analysis with WLS |
tssemParaVar | Estimate the heterogeneity (SD) of the parameter estimates of the TSSEM object |
uniR1 | First Stage analysis of the univariate R (uniR) approach |
uniR2lavaan | Second Stage analysis of the univariate R (uniR) approach |
uniR2mx | Second Stage analysis of the univariate R (uniR) approach |
vanderPol17 | Dataset on the effectiveness of multidimensional family therapy in treating adolescents with multiple behavior problems |
VarCorr | Extract Variance-Covariance Matrix of the Random Effects |
vcov.meta | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.meta3LFIML | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.mxRAMmodel | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.osmasem | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.reml | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.tssem1FEM | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.tssem1FEM.cluster | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.tssem1REM | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.wls | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vcov.wls.cluster | Extract Covariance Matrix Parameter Estimates from Objects of Various Classes |
vec2symMat | Convert a Vector into a Symmetric Matrix |
wls | Conduct a Correlation/Covariance Structure Analysis with WLS |
wvs94a | Forty-four Studies from Cheung (2013) |
wvs94b | Forty-four Covariance Matrices on Life Satisfaction, Job Satisfaction, and Job Autonomy |