Qrho | R Documentation |
Provides a chi-square test for significant variation in sample weighted correlation corrected for attenuating artifacts
Qrho(x, aproxe = FALSE)
x |
A matrix or data.frame with columns Rxy, n and artifacts (Rxx, Ryy, u):
see |
aproxe |
Logical test to determine if the approximate or exact var e is used |
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.
A table containing the following items:
CHISQ |
Chi-square value |
df |
degrees of freedom |
p-val |
probabilty value |
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.
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
Thomas D. Fletcher t.d.fletcher05@gmail.com
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.
varr
, vare
, rbar
,
CredIntRho
, pvse
# From Arthur et al
data(ABHt32)
Qrho(ABHt32)
# From Hunter et al
data(HSJt35)
Qrho(HSJt35)
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