psychometric (version 2.2)

Qrbar: Meta-Analytic Q statistic for r-bar

Description

Provides a chi-square test for significant variation in sample weighted correlation, rbar

Usage

Qrbar(x)
aprox.Qrbar(x)

Arguments

x

A matrix or data.frame with columns Rxy and n: see EnterMeta

Value

• A table containing the following items:
• CHISQ
  Chi-square value
• df
  degrees of freedom
• p-val
  probabilty value

Warning

The test is presented by Hunter et al. 1982, but is NOT recommended nor mentioned by Hunter & Schmidt (2004). The test is sensitive to the number of studies included in the meta-analysis. Large meta-analyses may find significant Q statistics when variation in the population is not present, and small meta-analyses may find lack of significant Q statistics when moderators are present. Hunter & Schmidt (2004) recommend the credibility inteval, CredIntRho, or the 75% rule, pvse, as determinants of the presence of moderators.

Details

Q is distributed as chi-square with df equal to the number of studies - 1. Multiple equations exist presumably because of a need to do the calculations by hand in the past. A significant Q statistic implies the presence of one or more moderating variables operating on the observed correlations.

References

Arthur, Jr., W., Bennett, Jr., W., and Huffcutt, A. I. (2001) Conducting Meta-analysis using SAS. Mahwah, NJ: Erlbaum. Hunter, J.E. and Schmidt, F.L. (2004). Methods of meta-analysis: Correcting error and bias in research findings (2nd ed.). Thousand Oaks: Sage Publications. Hunter, J.E., Schmidt, F.L., and Jackson, G.B. (1982). Meta-analysis: Cumulating research findings across studies. Beverly Hills: Sage Publications.

See Also

varr, vare, rbar, CredIntRho, pvse

Examples

# From Arthur et al
data(ABHt32)
aprox.Qrbar(ABHt32)

# From Hunter et al
data(HSJt35)
Qrbar(HSJt35)
aprox.Qrbar(HSJt35)