Charles E. Lance

A Review and Synthesis of the Measurement Invariance Literature: Suggestions, Practices, and Recommendations for Organizational Research

The establishment of measurement invariance across groups is a logical prerequisite to conducting substantive cross-group comparisons (e.g., tests of group mean differences, invariance of structural parameter estimates), but measurement invariance is rarely tested in organizational research. In this article, the authors (a) elaborate the importance of conducting tests of measurement invariance across groups, (b) review recommended practices for conducting tests of measurement invariance, (c) review applications of measurement invariance tests in substantive applications, (d) discuss issues involved in tests of various aspects of measurement invariance, (e) present an empirical example of the analysis of longitudinal measurement invariance, and (f) propose an integrative paradigm for conducting sequences of measurement invariance tests.

The Sources of Four Commonly Reported Cutoff Criteria What Did They Really Say

Everyone can recite methodological “urban legends” that were taught in graduate school, learned over the years through experience publishing, or perhaps just heard through the grapevine. In this article, the authors trace four widely cited and reported cutoff criteria to their (alleged) original sources to determine whether they really said what they are cited as having said about the cutoff criteria, and if not, what the original sources really said. The authors uncover partial truths in tracing the history of each cutoff criterion and in the end endorse a set of 12 specific guidelines for effective academic referencing provided by Harzing that, if adopted, should help prevent the further perpetuation of methodological urban legends.

Generational Differences in Work Values: Leisure and Extrinsic Values Increasing, Social and Intrinsic Values Decreasing:

Organizations are currently facing the retirement of many older workers and the challenge of recruiting and retaining young talent. However, few studies have empirically substantiated generational differences in work values. This study examines the work values of a nationally representative sample of U.S. high school seniors in 1976, 1991, and 2006 (N = 16,507) representing Baby Boomers, Generation X (GenX), and Generation Me (GenMe, also known as GenY, or Millennials). With data collected across time, these analyses isolate generational differences from age differences, unlike one-time studies, which cannot separate the two. Leisure values increased steadily over the generations (d comparing Boomers and GenMe = .57), and work centrality declined. Extrinsic values (e.g., status, money) peaked with GenX but were still higher among GenMe than among Boomers (d = .26). Contrary to popular press reports, GenMe does not favor altruistic work values (e.g., helping, societal worth) more than previous generations. Social values (e.g., making friends) and intrinsic values (e.g., an interesting, results-oriented job) were rated lower by GenMe than by Boomers. These findings have practical implications for the recruitment and management of the emerging workforce.

Examining the Causal Order of Job Satisfaction and Organizational Commitment

Four hypotheses have been advanced regarding the causal relationship between job satisfaction and organizational commitment: (a) satisfaction causes commitment, (b) commitment causes satisfaction, (c) satisfaction and commitment are reciprocally related, and (d) no causal relationship exists between the two constructs. These four hypotheses were represented by separate structural equation models in a longitudinal research design. Using a sample of management information systems professionals, the models were tested using a combination of pseudo-generalized least squares, and full information maximumlikelihood estimation procedures. The latter procedures controlled for the unmeasured causal variables problem characterizing past studies. Results supported the commitment-causes-satisfaction model.

Residual centering, exploratory and confirmatory moderator analysis, and decomposition of effects in path models containing interactions.

Hierarchical moderated regression (HMR) analysis may lead to interpretational problems in tests of mod erator (interaction) hypotheses. An alternative, resid ual-centering approach is described and compared to traditional HMR analysis. Procedures for evaluating in teraction hypotheses and general effect analysis proce dures are described for path (causal) models contain ing interactions. Index terms: Confirmatory analysis, Effect analysis in path models, Goodness-of- fit tests, Hierarchical moderated regression, Media tors, Moderated regression, Multicollinearity, Path models, Residual centering.

Risk factors for potentially harmful informal caregiver behavior.

Objectives: Caring for a sick or disabled relative has been linked to compromised caregiver health, and risk factors for negative caregiver outcomes have been studied extensively, but little attention has been given to care recipient and caregiver health as risk factors for potentially harmful behavior by informal caregivers. This article explores such risk factors.

Method Effects, Measurement Error, and Substantive Conclusions

Common method variance is routinely viewed as a pervasive problem in organizational research, one that undermines good science and biases empirical conclusions. The authors review research that has used multitrait-multimethod (MTMM) designs to estimate the magnitude of common method variance in organizational research. The results of this study show that method variance accounts for less variance (18%) than has been suggested by previous reviews. The authors also consider simultaneously the attenuating effect of measurement error with the inflationary effect of common method variance on observed relationships. Results indicate that although common method variance does have an inflationary effect on observed relationships, this effect is almost completely offset by the attenuating effect of measurement error.

A critique of the correlated trait-correlated method and correlated uniqueness models for multitrait-multimethod data.

The correlated trait-correlated method (CT-CM) and correlated uniqueness (CU) confirmatory factor analysis models for multitrait-multimethod data are critiqued. Although the CU model often returns convergent and admissible factor solutions when the CT-CM model does not, the CU model is shown to have theoretical and substantive shortcomings. On the basis of this critique, the authors recommend that the CT-CM model be regarded as the generally preferred model and that the CU model be invoked only when the CT-CM model fails.

What is method variance and how can we cope with it? A panel discussion

A panel of experts describes the nature of, and remedies for, method variance. In an attempt to help the reader understand the nature of method variance, the authors describe their experiences with method variance both on the giving and the receiving ends of the editorial review process, as well as their interpretation of other reviewers’ comments. They then describe methods of data analysis and research design, which have been used for detecting and eliminating the effects of method variance. Most methods have some utility, but none prevent the researcher from making faulty inferences. The authors conclude with suggestions for resolving disputes about method variance.

Revised Estimates of Dimension and Exercise Variance Components in Assessment Center Postexercise Dimension Ratings

The authors reanalyzed assessment center (AC) multitrait-multimethod (MTMM) matrices containing correlations among postexercise dimension ratings (PEDRs) reported by F. Lievens and J. M. Conway (2001). Unlike F. Lievens and J. M. Conway, who used a correlated dimension-correlated uniqueness model, we used a different set of confirmatory-factor-analysis-based models (1-dimension-correlated Exercise and 1-dimension-correlated uniqueness models) to estimate dimension and exercise variance components in AC PEDRs. Results of reanalyses suggest that, consistent with previous narrative reviews, exercise variance components dominate over dimension variance components after all. Implications for AC construct validity and possible redirections of research on the validity of ACs are discussed.