计量经济分析 = Econometric analysis

Summary

The use of both linear and generalized linear mixed-effects models (LMMs and GLMMs) has become popular not only in social and medical sciences, but also in biological sciences, especially in the field of ecology and evolution. Information criteria, such as Akaike Information Criterion (AIC), are usually presented as model comparison tools for mixed-effects models.


The presentation of ‘variance explained’ (R2) as a relevant summarizing statistic of mixed-effects models, however, is rare, even though R2 is routinely reported for linear models (LMs) and also generalized linear models (GLMs). R2 has the extremely useful property of providing an absolute value for the goodness-of-fit of a model, which cannot be given by the information criteria. As a summary statistic that describes the amount of variance explained, R2 can also be a quantity of biological interest.


One reason for the under-appreciation of R2 for mixed-effects models lies in the fact that R2 can be defined in a number of ways. Furthermore, most definitions of R2 for mixed-effects have theoretical problems (e.g. decreased or negative R2 values in larger models) and/or their use is hindered by practical difficulties (e.g. implementation).


Here, we make a case for the importance of reporting R2 for mixed-effects models. We first provide the common definitions of R2 for LMs and GLMs and discuss the key problems associated with calculating R2 for mixed-effects models. We then recommend a general and simple method for calculating two types of R2 (marginal and conditional R2) for both LMMs and GLMMs, which are less susceptible to common problems.


This method is illustrated by examples and can be widely employed by researchers in any fields of research, regardless of software packages used for fitting mixed-effects models. The proposed method has the potential to facilitate the presentation of R2 for a wide range of circumstances.

https://besjournals.onlinelibrary.wiley.com/doi/epdf/10.1111/j.2041-210x.2012.00261.x

A general and simple method for obtaining R2 from generalized linear mixed-effects models

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 structura...

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

The field of organizationa l justice continues to be marked by several important research questions, including the size of relationships among justice dimensions, the relative importance of different justice criteria, and the unique effects of justice dimensions on key outcomes. To address such questions, the authors conducted a meta-analytic review of 183 justice studies. The results suggest that although different justice dimensions are moderately to highly related, they contribute incremental variance explained in fairness perceptions. The results also illustrate the overall and unique relationships among distributive, procedural, interpersonal, and informational justice and several organizational outcomes (e.g., job satisfaction, organizational commitment, evaluation of authority, organizational citizenship behavior, withdrawal, performance). These findings are reviewed in terms of their implications for future research on organizationa l justice.

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Justice at the millennium: a meta-analytic review of 25 years of organizational justice research

Pedagosko i psiholosko testiranje i procjenjivanje spadaju među najvažnije doprinose znanosti o ponasanju nasem drustvu i pružaju temeljna i znacajna poboljsanja u odnosu na ranije postupke. Iako se ne može ustvrditi da su svi testovi dovoljno usavrseni niti da su sva testiranja razborita i korisna, postoji velika kolicina informacija koje ukazuju na ucinkovitost kvalitetnih instrumenata u onim situacijama u kojima je njihovo koristenje potkrijepljeno validacijskim podacima. Pravilna upotreba testova može dovesti do boljih odluka o pojedincima i programima nego sto bi to bio slucaj bez njihovog koristenja, a također i ukazati na put za siri i pravedniji pristup obrazovanju i zaposljavanju. Međutim, losa upotreba testova može dovesti do zamjetne stete nanesene ispitanicima i drugim sudionicima u procesu donosenja odluka na temelju testovnih podataka. Cilj Standarda je promoviranje kvalitetne i eticne upotrebe testova te uspostavljanje osnovice za ocjenu kvalitete postupaka testiranja. Svrha objavljivanja Standarda je uspostavljanje kriterija za evaluaciju testova, provedbe testiranja i posljedica upotrebe testova. Iako bi evaluacija prikladnosti testa ili njegove primjene trebala ovisiti prvenstveno o strucnim misljenjima, Standardi pružaju okvir koji osigurava obuhvacanje svih relevantnih pitanja. Bilo bi poželjno da svi autori, sponzori, nakladnici i korisnici profesionalnih testova usvoje Standarde te da poticu druge da ih također prihvate.

Standards for educational and psychological testing

Research in strategic human resource management (SHRM) has evolved over the past 30 years to become more theory based and to exhibit greater empirical rigor. However, much has changed in the external environment that makes the existing theories, approaches, and methodologies inappropriate for addressing the questions that organizations face in managing their human resources today. In this chapter we discuss a number of environmental changes impacting organizations and identify tensions that researchers have faced in exploring how firms seek to manage their people as a source of competitive advantage. We argue that past research has focused on only one side of the tension at a time, thus limiting the usefulness of the answers that research provides. We advocate for research that simultaneously addresses both sides of the tensions in a way that can revolutionize research in SHRM.

A Research Revolution in SHRM: New Challenges and New Research Directions

Construct clarity:Multidisciplinary considerations and an illustration using human capital

This study applied the attribution framework described by Weiner (1986) to understand the psychological reasons applicants withdrew from a police officer selection process, as well as the consequences of their attributions for withdrawal. Individuals (n= 196) who withdrew from the selection process were contacted and were asked to indicate their primary reason for withdrawal; and then rated this reason on locus, stability, and controllability dimensions. They also reported future application expectancies. Results indicate minority and female applicants appeared to indicate different reasons for withdrawing than did White and male applicants. Finally, race and controllability interacted in the prediction of reapplication expectancies, such that the relationship between expectancies and controllability was negative for White applicants and positive for minority applicants.

Examining Applicants’ Attributions for Withdrawal From a Selection Procedure

Research has shown that explanations for selection decisions may influence a variety of applicant perceptions and behavior, but an understanding of how and why this occurs remains largely unknown. This study attempts to understand the effects of explanations by adopting Kelley's (1967, 1972) covariation model of the attribution process. Specifically, explanations that vary on consensus, distinctiveness, and consistency covariation information should produce predictable effects on applicant perceptions and attributions. Results from 2 studies, the first a laboratory study and the second a field study with actual applicants, support the utility of the covariation model for understanding the influence of explanations for selection decisions on locus attributions, fairness, self-perceptions, and organizational attractiveness. These results suggest that the covariation model may be a useful means to construe the explanation-attribution-perception relationship, and thus provide a number of theoretical and practical implications.

Robert E. Ployhart

Papers

A Research Revolution in SHRM: New Challenges and New Research Directions

Construct clarity:Multidisciplinary considerations and an illustration using human capital

Examining Applicants’ Attributions for Withdrawal From a Selection Procedure

Using Attributions to Understand the Effects of Explanations on Applicant Reactions: Are Reactions Consistent With the Covariation Principle?1

Assessing Personality With Situational Judgment Measures