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.

/pdf/justice-at-the-millennium-a-meta-analytic-review-of-25-years-b9qfmr75n2.pdf

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

Many studies in the social and organizational sciences are concerned with estimating and testing between-group mean differences. Typically, responses to these scales are summed, and the summed score or the mean of the summed score is then compared across groups using standard statistical tests ( t tests) and described using d values. Even though there is a call for establishing measurement invariance prior to examining mean differences, very few studies seem to follow this advice. In this study, the authors extend prior invariance work to demonstrate how a lack of invariance can obscure the effect size, direction, and statistical significance of mean differences. In particular, the authors show how manifest mean differences can be exaggerated, reduced, or even switch in direction relative to latent mean differences. Thus, they emphasize the statistical and substantive consequences that may occur when the scales used to perform mean comparisons do not possess measurement invariance.

The Analysis of Mean Differences Using Mean and Covariance Structure Analysis Effect Size Estimation and Error Rates

The purpose of this article is to simultaneously advance theory and practice by understanding how the Coronavirus disease 2019 (COVID-19) pandemic relates to new hire engagement. Prior research suggests starting a new job is an uncertain experience; we theorize that the COVID-19 pandemic creates additional environmental stressors that affect new hire engagement. First, we hypothesize that the occurrence of COVID-19 and unemployment rates relate negatively to engagement. Second, we theorize that the effects of the pandemic become more disruptive on new hire engagement as they gain tenure within the organization. Third, drawing from strategic management theory, we test whether States that introduce stronger COVID-19 policies help enhance the engagement of new hires. Examining a U.S. national sample of 12,577 newly hired (90 days or less) quick service restaurant employees across 9 months (January-September, 2020), we find support for these hypotheses. Subsequent model comparisons suggest there may be health stressors that shape engagement more strongly than purely economic stressors. These findings may be important because they highlight the experiences of workers more likely to be exposed to the pandemic and affected by COVID-related policies. Should the results generalize to other samples and jobs, this study offers potentially new research directions for understanding relationships between macro stressors and new hire perceptions and socialization. It also offers practical implications by helping organizations understand the importance of explicitly managing job insecurity, particularly in terms of COVID-19 policy. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The COVID-19 pandemic and new hire engagement: Relationships with unemployment rates, state restrictions, and organizational tenure.

Personnel Selection: Ensuring Sustainable Organizational Effectiveness Through the Acquisition of Human Capital

This study proposes that reaching applicants through more diagnostic recruitment sources earlier in their educational development (e.g., in high school) can lead them to invest more in their occupation-specific human capital (OSHC), thereby making them higher quality candidates. Using a sample of 78

Using Recruitment Source Timing and Diagnosticity to Enhance Applicants' Occupation-Specific Human Capital.

Although the service-profit chain posits that employees and customers are interrelated at the unit level (Heskett, Sasser, & Schlesinger, 1997), most theory and practice give primary emphasis to the employee. In this study, we sought to draw attention to the relatively neglected influence that customers may collectively have on employees. Specifically, we examined how collective customer perceptions of service quality relate to collective employee job satisfaction, service climate, and collective turnover (voluntary and involuntary). Using a sample of 294 bank branches, 1,975 employees, and 52,920 customers, modeled at the branch level over 2 years, we found that collective customer perceptions of service quality produced a stronger effect on collective employee job satisfaction and service climate than vice versa. We also provided the first tests demonstrating that collective customer perceptions of service quality significantly and independently influence collective voluntary turnover, even while simultaneously modeling collective employee job satisfaction and service climate. Further, we showed that the effects of collective turnover (voluntary and involuntary) are primarily related to collective customer perceptions and service climate, but through different paths. Although the turnover base rates are modest, these empirical findings highlight the role that collective customer perceptions can have in shaping collective employee attitudes, climate, and turnover and, thus, should be considered and replicated in future theory and research. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

The neglected role of collective customer perceptions in shaping collective employee satisfaction, service climate, voluntary turnover, and involuntary turnover: A cautionary note

Robert E. Ployhart

Papers

The Analysis of Mean Differences Using Mean and Covariance Structure Analysis Effect Size Estimation and Error Rates

The COVID-19 pandemic and new hire engagement: Relationships with unemployment rates, state restrictions, and organizational tenure.

Personnel Selection: Ensuring Sustainable Organizational Effectiveness Through the Acquisition of Human Capital

Using Recruitment Source Timing and Diagnosticity to Enhance Applicants' Occupation-Specific Human Capital.

The neglected role of collective customer perceptions in shaping collective employee satisfaction, service climate, voluntary turnover, and involuntary turnover: A cautionary note