Using Hierarchical Linear Models to Examine Moderator Effects: Person-by-Organization Interactions

Mark L. Davison, Nohoon Kwak, Young Seok Seo, Jiyoung Choi

Research output: Contribution to journalArticlepeer-review

46 Scopus citations

Abstract

A cross-level interaction is said to occur when the effects of client or employee characteristics interact with organizational characteristics to influence an employee or client outcome variable. Hierarchical linear modeling (HLM) is briefly described, particularly as it applies to the study of cross-level interactions. HLM is then compared to moderated multiple regression (MMR). An HLM model incorporating cross-level interactions is illustrated with data from a study of test validity across organizational units. An HLM model for person-organization congruence is then described. As compared to MMR, HLM can more readily handle large numbers of organizations. By increasing the number of organizations that can be studied, HLM should increase the power of the designs that researchers can use.

Original languageEnglish (US)
Pages (from-to)231-254
Number of pages24
JournalOrganizational Research Methods
Volume5
Issue number3
DOIs
StatePublished - Jul 2002

Bibliographical note

Copyright:
Copyright 2005 Elsevier B.V., All rights reserved.

Fingerprint

Dive into the research topics of 'Using Hierarchical Linear Models to Examine Moderator Effects: Person-by-Organization Interactions'. Together they form a unique fingerprint.

Cite this