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Constructing and evaluating behavioral science models is a complex process. Decisions must be made about which variables to include, which variables are related to each other, the functional forms of the relationships, and so on. The last 10 years have seen a substantial extension of the range of statistical tools available for use in the construction process. The progress in tool development has been accompanied by the publication of handbooks that introduce the methods in general terms (Arminger et al., 1995; Tinsley & Brown, 2000a). Each chapter in these handbooks cites a wide range of books and articles on specific analysis topics.

Self-report questionnaires are the predominant method used in human resource management (HRM) research to assess employees’ work-related psychological constructs (e.g., processes, states, and attributes). However, this method is associated with significant shortcomings, including the introduction of self-serving bias and common method variance when used exclusively. In this chapter, the authors challenge the assumption that individuals themselves are the only accurate source of the self-focused information collected in HRM research. Instead, the authors propose that other-ratings – ratings of a target individual that are provided by a workplace observer, such as a coworker, supervisor, or subordinate – can accurately assess commonly measured work-related psychological constructs. The authors begin by explaining the advantages of other-ratings for HRM research and practice, reviewing the history of other-ratings and how they emerged in the personality and person-perception literature, and outlining how they have been used in HRM research to date. Then, the authors build upon Funder’s (1995) realistic accuracy model to develop a theoretical argument detailing why workplace others should be able to accurately judge how another employee thinks and feels about work. Next, the authors highlight existing evidence in the literature on the accuracy of other-ratings and present the results of a preliminary meta-analysis on the ability of other-ratings to predict self-ratings of work-related psychological constructs. Finally, the authors discuss potential moderators of other-rating accuracy and reflect on a number of practical considerations for researchers looking to use other-ratings in their own work. The authors intend for this chapter to meaningfully contribute to the larger conversation on HRM research methods. Other-ratings are a simple, yet powerful, addition to the methodological toolkit of HRM researchers that can increase flexibility in research design and improve the overall quality of research.

The purpose of this chapter is to provide researchers a summary of some of the latest developments in item response theory (IRT), and to help these groups realize that psychometric tools can now be used for theory testing in addition to the traditional role of improving construct measurement. The author first reviews some of the fundamental tenets of classical test theory to contrast with IRT. He then describes recent advances in goodness-of-fit tests that have helped turn IRT into a model-testing tool. Finally, the author reviews several new test models that provide new flexibilities, summarizing summarize several examples of research that has used these new models in organizational research. At the end of this review, the author provides suggestions to help researchers better use these new IRT tools. Although there have been significant advances in IRT in the past decade, there has not been a systematic review of these developments. This review places those developments in context to provide readers a real appreciation of these breakthroughs.

Organizational researchers have become increasingly interested in multi-level constructs – that is, constructs that are meaningful at multiple levels of analysis. However, despite the plethora of theoretical and empirical work on multi-level topics, explicit frameworks for validation of multi-level constructs have yet to be fully developed. Moreover, available principles for conducting construct validation assume that the construct resides at a single level of analysis. We propose a five-step framework for conceptualizing and testing multi-level constructs by integrating principles of construct validation with recent advancements in multi-level theory, research, and methodology. The utility of the framework is illustrated using theoretical and empirical examples.

This chapter presents empirical evidence on the effects of attributional retraining (AR), a motivation-enhancing treatment that can offset maladaptive explanatory mind-sets arising from adverse learning experiences. The evidence shows that AR is effective for assisting college students to adapt to competitive and challenging achievement settings.

This chapter describes the characteristics of AR protocols and details three primary advances in studying AR efficacy in terms of achievement performance, psychosocial outcomes, and processes that mediate AR-performance linkages. The psychological mechanisms that underpin AR effects on motivation and performance are outlined from the perspective of Weiner’s (1974, 1986, 2012) attribution theory.

Laboratory and field studies show that AR treatments are potent interventions that have short-term and long-lasting psychosocial, motivation, and performance benefits in achievement settings. Students who participate in AR programs are better off than their no-AR counterparts not just in their cognitive and affective prospects, but they also outperform their no-AR peers in class tests, course grades, and grade-point-averages, and are more persistent in terms of course credits and graduation rates.

This paper contributes to the emerging literature on treatment interventions in achievement settings by documenting key advances in the development of AR protocols and by identifying the next steps critical to moving the literature forward. Further progress in understanding AR efficacy will rest on examining the analysis of complex attributional thinking, the mediation of AR treatment effects, and the boundary conditions that moderate AR treatment efficacy.

The chapter begins by presenting a case study of a 4th grade student, who has been referred by his teacher for an evaluation. However before this case can be completely understood, it is necessary to understand the limitations associated with the general intelligence approach of assessment. The chapter provides an overview of these limitations and suggests using a processing-based approach instead of a general intelligence approach. The second section outlines the Planning, Attention, Simultaneous, and Successive (PASS) theory and approach toward assessment, which is supported by neuropsychological research. The final section returns to the case study and demonstrates how the information gathered using the PASS theory and Cognitive Assessment System (CAS) can be used to guide interventions for various learning disabilities.