Advanced Search

Journal Navigation

Journal Home

Subscriptions

Archive

Contact Us

Table of Contents

SAGETRACK

Sign In to gain access to subscriptions and/or personal tools.
Organizational Research Methods
This Article
Right arrow Full Text (PDF)
Right arrow References
Right arrow Alert me when this article is cited
Right arrow Alert me if a correction is posted
Services
Right arrow Email this article to a friend
Right arrow Similar articles in this journal
Right arrow Similar articles in Web of Science
Right arrow Alert me to new issues of the journal
Right arrow Add to Saved Citations
Right arrow Download to citation manager
Right arrowRequest Permissions
Right arrow Request Reprints
Right arrow Add to My Marked Citations
Citing Articles
Right arrow Citing Articles via Google Scholar
Right arrow Citing Articles via Scopus
Google Scholar
Right arrow Articles by Han, J.
Right arrow Search for Related Content
Social Bookmarking
 Add to CiteULike   Add to Complore   Add to Connotea   Add to Del.icio.us   Add to Digg   Add to Reddit   Add to Technorati   Add to Twitter  
What's this?

Crossover Linear Modeling: Combining Multilevel Heterogeneities in Crossover Relationships

Jian Han

Peking University

In organizational research, many multilevel structures are not fully nested but have a crossover structure. For example, in early recruitment study, the relationship between job applicants and recruiting companies has the crossover structure because each applicant is interested in applying multiple companies whereas each company is of interest to multiple applicants, and applicants and companies are not fully nested within each other. This article introduces the crossover linear modeling (CLM) method and argues that CLM is useful when dealing with multilevel crossover structures by combining the heterogeneities of all levels into one model. The article uses an example in early recruitment research to illustrate the use of CLM in modeling direct effects, cross-level effects, and interaction effects in a crossover data structure. The statistical analysis on an actual data set shows that CLM is able to identify both company-level and applicant-level heterogeneities. The article presents further examples to show that CLM can be applied to many organizational research settings when multilevel crossover structures are present.

Key Words: multilevel analysis • crossover linear modeling • random coefficient modeling • hierarchical linear modeling • early recruitment study

Organizational Research Methods, Vol. 8, No. 3, 290-316 (2005)
DOI: 10.1177/1094428105278177


Add to CiteULike CiteULike   Add to Complore Complore   Add to Connotea Connotea   Add to Del.icio.us Del.icio.us   Add to Digg Digg   Add to Reddit Reddit   Add to Technorati Technorati   Add to Twitter Twitter    What's this?