1998
DOI: 10.1177/109442819800100105
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Correcting Turnover Correlations: A Critique

Abstract: In this article, the authors argue that turnover correlations do not need to be corrected. First, they maintain that correction formulas cannot correct for poor construct validity. Second, they discuss the original purposes of turnover correction formulas. Third, the authors describe the logical fallacies of correcting turnover correlations. Finally, they show why turnover correlations are not, as is widely believed, statistically limited to a maximum of .80.

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Cited by 4 publications
(3 citation statements)
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References 35 publications
(41 reference statements)
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“…When studies did not report internal consistency reliability, we used the mean of reliability estimates of other primary studies (see Table 1). No corrections were applied to address variable base rates for employment status, because this is a truly dichotomous variable (e.g., Williams & Peters, 1998). Based on previous research (Frazier, Fainshmidt, Klinger, Pezeshkan, & Vracheva, 2017; Oh et al, 2014), we set the cutoff for the minimum number of primary studies to warrant interpretation of the meta-analytic correlations at three in the main analyses and two in the moderator analyses.…”
Section: Methodsmentioning
confidence: 99%
“…When studies did not report internal consistency reliability, we used the mean of reliability estimates of other primary studies (see Table 1). No corrections were applied to address variable base rates for employment status, because this is a truly dichotomous variable (e.g., Williams & Peters, 1998). Based on previous research (Frazier, Fainshmidt, Klinger, Pezeshkan, & Vracheva, 2017; Oh et al, 2014), we set the cutoff for the minimum number of primary studies to warrant interpretation of the meta-analytic correlations at three in the main analyses and two in the moderator analyses.…”
Section: Methodsmentioning
confidence: 99%
“…Within the conversion process, one must pay close attention to the proportions of the groups involved (e.g., Blacks and Whites). This is because d is not influenced by the proportion of individuals in different groups, but r is influenced by such proportions (see Williams, 1990, and Williams & Peters, 1998, for discussions of this issue). Given that the correction formulas are written for r , it is important to either compute the point-biserial r directly or to “embed” the correct information in the conversion process if one is converting an observed d to an observed r (see Hunter & Schmidt, 1990, p. 273, or Bobko et al, 2001).…”
Section: Issues In Correcting Standardized Ethnic Group Differencesmentioning
confidence: 99%
“…(2014), this review of methodological approaches shows increased use of highly sophisticated measurement and data analysis techniques in studying turnover. This sophistication was evident from early discussions on the use of survival analysis (Van der Merwe & Miller, 1971), to correcting turnover correlations (Williams & Peters, 1998) and increased use of model‐testing techniques such as structural equation modelling and path analysis (Allen et al., 2014). However, such approaches focus on prediction and control rather than more nuanced understanding, and separate the employee from the employment context, thereby leaving out important details of the ‘realities of the employment relation[ship]’ (Godard, 2014, p. 10).…”
Section: Discussionmentioning
confidence: 99%