Simulated Effect Sizes Reported by Hox (2002)

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Description

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

Usage

1

Details

The variables are:

study

Study number

yi

Effect size (standardized mean difference)

vi

Sampling variance of the effect size

weeks

Duration of the experimental intervention in terms of weeks

Source

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

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

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## 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)

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