Christopher J. Lake

Using Mixed-Model Item Response Theory to Analyze Organizational Survey Responses: An Illustration Using the Job Descriptive Index

In this article, the authors illustrate the use of mixed-model item response theory (MM-IRT) and explain its usefulness for analyzing organizational surveys. The authors begin by giving an overview of MM-IRT, focusing on both technical aspects and previous organizational applications. Guidance is provided on how researchers can use MM-IRT to check scoring assumptions, identify the influence of systematic responding that is unrelated to item content (i.e., response sets), and evaluate individual and group difference variables as predictors of class membership. After summarizing the current body of research using MM-IRT to address problems relevant to organizational researchers, the authors present an illustration of the use of MM-IRT with the Job Descriptive Index (JDI), focusing on the use of the ‘‘?’’ response option. Three classes emerged, one most likely to respond in the positive direction, one most likely to respond in the negative direction, and another most likely to use the ‘‘?’’ response. Trust in management, job tenure, age, race, and sex were considered as correlates of class membership. Results are discussed in terms of the applicability of MM-IRT and future research endeavors.

Understanding the Relation Between Attitude Involvement and Response Latitude Using Item Response Theory

Adapting the original latitude of acceptance concept to Likert-type surveys, response latitudes are defined as the range of graded response options a person is willing to endorse. Response latitudes were expected to relate to attitude involvement such that high involvement was linked to narrow latitudes (the result of selective, careful responding) and low involvement was linked to wide latitudes (the result of disinterested, careless responding). In an innovative application of item response theory, parameters from Samejima’s graded response model were used to examine response latitude width. Other item response theory–based tools (e.g., test characteristic curves, information functions) were used to examine the influence of response latitudes on the psychometric functioning of several attitude surveys. A mix of experimental and nonexperimental methods was employed to create groups of high and low involvement surveys. Comparisons of these surveys showed that high involvement was related to significantly narrower response latitudes than low involvement. Furthermore, wide response latitudes were related to unfavorable psychometric properties such as reduced survey discrimination and reduced internal validity relative to narrow latitudes. Comparisons of information functions in high and low involvement conditions, however, were less consistent. Implications of wide response latitudes are quite unfavorable for researchers and suggest that an element of error is present when respondents feel little involvement with an attitude topic.

Validation of the Job-Hopping Motives Scale:

Job-hopping is the practice of making frequent voluntary job changes. Integrating theory and research from career and organizational turnover research, two distinct motives for job-hopping were proposed. The escape motive describes frequently changing jobs to escape disliked work environments, whereas the advancement motive describes frequently changing jobs as a means of career advancement. A self-report measure of job-hopping motives was developed and validated using responses from 221 students and 1,528 adults. Factor analysis showed that the motives are distinct but moderately related. The escape motive was associated with negative reactivity (impulsivity, negative affect) and script-based turnover decisions. The advancement motive was associated with positive proactivity (persistence, growth need strength), and protean, boundaryless, and kaleidoscope career theory components. Both motives were associated with organizational withdrawal, quick turnover decisions, and increased turnover. Job-hopping motives predicted historic job change rate over and above demographic, career, and organizational turnover variables.