Qrho {psychometric}

Meta-Analytic Q statistic for rho

Description

Provides a chi-square test for significant variation in sample weighted correlation corrected for attenuating artifacts

Usage

Qrho(x, aproxe = FALSE)

Arguments

x

A matrix or data.frame with columns Rxy, n and artifacts (Rxx, Ryy, u): see EnterMeta

aproxe

Logical test to determine if the approximate or exact var e is used

Details

Q is distributed as chi-square with df equal to the number of studies - 1. A significant Q statistic implies the presence of one or more moderating variables operating on the observed correlations after corrections for artifacts.

Value

A table containing the following items:

CHISQ

Chi-square value

df

degrees of freedom

p-val

probabilty value

Warning

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.

Note

Q is defined as: (k*vr)/(vav+ve)

where, k is the number of studies, vr is varr, vav is varAV, and ve is vare

Author(s)

Thomas D. Fletcher [e-mail]

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)
Qrho(ABHt32)

# From Hunter et al
data(HSJt35)
Qrho(HSJt35)