metaSEM (version 0.9.10)

Hox02: Simulated Effect Sizes Reported by Hox (2002)

Description

Twenty stimulated studies on standardized mean difference and one continuous study characteristic reported by Hox (2002).

Usage

data(Hox02)

Source

Hox, J. J. (2002). Multilevel analysis: Techniques and applications. Mahwah, N.J.: Lawrence Erlbaum Associates.

Details

The variables are:

References

Cheung, M. W.-L. (2008). A model for integrating fixed-, random-, and mixed-effects meta-analyses into structural equation modeling. Psychological Methods, 13, 182-202.

Examples

## Not run: 
# data(Hox02)
# 
# #### ML estimation method
# ## Random-effects meta-analysis
# summary( meta(y=yi, v=vi, data=Hox02, I2=c("I2q", "I2hm"), intervals.type="LB") ) 
# 
# ## Fixed-effects meta-analysis
# summary( meta(y=yi, v=vi, data=Hox02, RE.constraints=0,
#               model.name="Fixed effects model") )
# 
# ## Mixed-effects meta-analysis with "weeks" as a predictor
# ## Request likelihood-based CI
# summary( meta(y=yi, v=vi, x=weeks, data=Hox02, intervals.type="LB",
#               model.name="Mixed effects meta analysis with LB CI") )
# 
# #### REML estimation method
# ## Random-effects meta-analysis with REML
# summary( VarComp <- reml(y=yi, v=vi, data=Hox02) )
# 
# ## Extract the variance component
# VarComp_REML <- matrix( coef(VarComp), ncol=1, nrow=1 )
# 
# ## Meta-analysis by treating the variance component as fixed
# summary( meta(y=yi, v=vi, data=Hox02, RE.constraints=VarComp_REML) )
# 
# 
# ## Mixed-effects meta-analysis with "weeks" as a predictor
# ## Request likelihood-based CI
# summary( reml(y=yi, v=vi, x=weeks, intervals.type="LB",
#               data=Hox02, model.name="REML with LB CI") )
# ## End(Not run)