The link between employee attitudes and employee effectiveness: Data matrix of meta-analytic estimates based on 1161 unique correlations
verifiedrich profile · Data in Brief · 2016
Mackay, Michael M.
How this was studied
A meta-analytic synthesis — it pools many primary studies rather than running a single design, so there is no single-study diagram.
What this article reports
The findings we extracted from this work, normalized into Principia’s relationship form (X → Y). Each feeds the synthesized models below.
job involvement → turnover intention
job involvement → job satisfaction
Models this article informs
The meta-analytic priors this article contributes evidence to — its place in the broader synthesis.
job involvement correlates job satisfaction
job involvement correlates task performance
job involvement predicts job satisfaction
job involvement predicts task performance
job involvement predicts turnover intention
In the authors’ words
The article’s own abstract.
This article offers a correlation matrix of meta-analytic estimates between various employee job attitudes (i.e., Employee engagement, job satisfaction, job involvement, and organizational commitment) and indicators of employee effectiveness (i.e., Focal performance, contextual performance, turnover intention, and absenteeism). The meta-analytic correlations in the matrix are based on over 1100 individual studies representing over 340,000 employees. Data was collected worldwide via employee self-report surveys. Structural path analyses based on the matrix, and the interpretation of the data, can be found in "Investigating the incremental validity of employee engagement in the prediction of employee effectiveness: a meta-analytic path analysis" (Mackay et al., 2016) [1].
What the literature says about it
Attributed, open-access quotes from other works that cite this article, plus the citation-graph verdict tally. Corroborations and disputes, in one place — the honest-broker view.
No open-access quotations have been captured yet.
Assembled from Principia’s registry — bibliographic record, extracted effect sizes, the models they inform, and open-access citing literature.