In this panelist symposium we bring together scale development experts from various disciplines and research interests to discuss critical issues, emerging topics, and future directions in measurement. Each panelist, will present their view of a critical issue. In combination, the panelists’ views critique some aspects of current practice and highlight new directions in measurement development. After the panelists present their comments they will engage in discussion with attendees.
The purpose of the present article is to take stock of a recent exchange in Organizational Research Methods between critics and proponents of partial least squares path modeling (PLS-PM). The two target articles were centered around six principal issues, namely whether PLS-PM: (a) can be truly characterized as a technique for structural equation modeling (SEM), (b) is able to correct for measurement error, (c) can be used to validate measurement models, (d) accommodates small sample sizes, (e) is able to provide null hypothesis tests for path coefficients, and (f) can be employed in an exploratory, model-building fashion. We summarize and elaborate further on the key arguments underlying the exchange, drawing from the broader methodological and statistical literature to offer additional thoughts concerning the utility of PLS-PM and ways in which the technique might be improved. We conclude with recommendations as to whether and how PLS-PM serves as a viable contender to SEM approaches for estimating and evaluating theoretical models.
Abstract A growing body of research suggests a link between psychosocial factors and breast cancer. Research in this area often contains methodological problems, however, such as small sample size, inadequate comparison groups, omission of important control variables, inclusion of only a few psychosocial variables, and failure to analyze moderating effects. To overcome these problems, the present study examined the link between breast cancer and multiple psychosocial variables (life events, coping, Type A behavior pattern, availability of social support) among 1,052 women with and without breast cancer. After controlling for history of breast cancer and age, we found very few significant relationships between psychosocial variables and breast cancer. Furthermore, the relationship between life events and breast cancer was not moderated by coping, Type A, or availability of social support. Methodological and substantive reasons for these findings are discussed.
To study the changing nature of work, researchers need measures of work that are valid and comprehensive. One potentially useful measure of work is the Multimethod Job Design Questionnaire (MJDQ; Campion, 1988), which was developed to assess 4 general approaches to work design (i.e., motivational, mechanistic, biological, perceptual‐motor). Although the MJDQ holds promise as a general measure of work, little information is available regarding its psychometric properties. This study examines the MJDQ, using alternative hierarchical factor structures to represent work at varying levels of abstraction. Little support was found for the 4‐factor structure corresponding to the work design approaches underling the MJDQ or for various hierarchical factor structures that simultaneously depicted general and specific aspects of work. However, a 10‐factor first‐order model received good support and may provide a useful basis for scoring and interpreting the MJDQ in future research.
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