Testing interaction effects in LISREL: Examination and illustration of available procedures
Jose M Cortina, Gilad Chen, William P Dunlap. Organizational Research Methods. Thousand Oaks: Oct 2001. Vol. 4, Iss. 4; pg. 324, 37 pgsAbstract (Summary)
The concomitant proliferation of causal modeling and hypotheses of multiplicative effects has brought about a tremendous need for procedures that allow the testing of moderated structural equation models (MSEMs). The seminal work of Kenny and Judd and Hayduk has been drawn on by several authors in the past 10 years, thus producing procedures that allow for such tests. Yet, utilization of MSEMs in empirical research has been quite rare. The purposes of this article are twofold. First, it discusses general issues with respect to multivariate normality, indicators of latent products, the nature of latent products, and identification problems in MSEM. Second, it reviews and illustrates techniques that are available for the testing of interaction effects in structural equation models.

The Moderator-Mediator Variable Distinction in Social Psychological Research: Conceptual, Strategic, and Statistical Considerations
Baron, Reuben M, Kenny, David A. Journal of Personality and Social Psychology. Washington: Dec 1986. Vol. 51, Iss. 6; pg. 1173Abstract (Summary)
An attempt to distinguish between the properties of moderator and mediator variables at a number of levels is presented. A compendium of analytic procedures for making use of the moderator/mediator distinction is provided.p

Title:
An Overview of the Logic and Rationale of Hierarchical Linear Models.
Authors:
Hofmann, David A.1Source:
Journal of Management; 1997, Vol. 23 Issue 6, p723, 22p, 1 diagram
Document Type:
Article
Subject Terms:
*ORGANIZATIONAL behavior
*MATHEMATICAL statistics
*ORGANIZATIONAL structure
*GROUP decision making
*INDUSTRIAL organization
*TEAMS in the workplace
Abstract:
Due to the inherently hierarchical nature of organizations, data collected in organizations consist of nested entities. More specifically, individuals are nested in work groups, work groups are nested in departments, departments are nested in organizations, and organizations are nested in environments. Hierarchical linear models provide a conceptual and statistical mechanism for investigating and drawing conclusions regarding the influence of phenomena at different levels of analysis. This introductory paper: (a) discusses the logic and rationale of hierarchical linear models, (b) presents a conceptual description of the estimation strategy, and (c) using a hypothetical set of research questions, provides an overview of a typical series of multi-level models that might be investigated.

Title:The Problem of Measurement Model Misspecification in Behavioral and Organizational Research and Some Recommended Solutions.
Authors:
MacKenzie, Scott B.1 mackenz@indiana.edu
Podsakoff, Philip M.2
Jarvis, Cheryl Burke3
Source:
Journal of Applied Psychology; Jul2005, Vol. 90 Issue 4, p710-730, 21pDocument Type:
Article
Subject Terms:
*ORGANIZATIONAL behavior
*ESTIMATION theory
*ORGANIZATION
*RESEARCH
*MONTE Carlo method
*SIMULATION methods
*ORGANIZATIONAL structure
Abstract:
The purpose of this study was to review the distinction between formative- and reflective-indicator measurement models, articulate a set of criteria for deciding whether measures are formative or reflective, illustrate some commonly researched constructs that have formative indicators, empirically test the effects of measurement model misspecification using a Monte Carlo simulation, and recommend new scale development procedures for latent constructs with formative indicators. Results of the Monte Carlo simulation indicated that measurement model misspecification can inflate unstandardized structural parameter estimates by as much as 400% or deflate them by as much as 80% and lead to Type I or Type II errors of inference, depending on whether the exogenous or the endogenous latent construct is misspecified. Implications of this research are discussed.

Title:
Common Method Biases in Behavioral Research: A Critical Review of the Literature and Recommended Remedies.
Authors:
Podsakoff, Philip M.
MacKenzie, Scott B.
Jeong-Yeon Lee
Podsakoff, Nathan P.
Source:
Journal of Applied Psychology; Oct2003, Vol. 88 Issue 5, p879, 25p, 4 charts, 2 diagramsDocument Type:
Article
Subject Terms:
*PSYCHOLOGY
*RESEARCH
PREJUDICES
SOCIAL sciences
METHODOLOGY
NAICS/Industry Codes :
541720 Research and Development in the Social Sciences and Humanities
Abstract:
Interest in the problem of method biases has a long history in the behavioral sciences. Despite this, a comprehensive summary of the potential sources of method biases and how to control for them does not exist. Therefore, the purpose of this article is to examine the extent to which method biases influence behavioral research results, identify potential sources of method biases, discuss the cognitive processes through which method biases influence responses to measures, evaluate the many different procedural and statistical techniques that can be used to control method biases, and provide recommendations for how to select appropriate procedural and statistical remedies for different types of research settings.