This Article Full Text (PDF) References Alert me when this article is cited Alert me if a correction is posted Services Email this article to a friend Similar articles in this journal Alert me to new issues of the journal Add to Saved Citations Download to citation manager Request Permissions Request Reprints Add to My Marked Citations Citing Articles Citing Articles via Google Scholar Citing Articles via Scopus Google Scholar Articles by Locascio, J. J. Search for Related Content Social Bookmarking                         What's this?

The Cross-Lagged Correlation Technique: Reconsideration in Terms of Exploratory Utility, Assumption Specification and Robustness

Northwestern University

The cross-lagged correlation technique (CLC) for assessing causality from passive observational data has been the subject of much recent criticism. CLC compares cross correlations between variables across time points of measurement and attributes differences in correlations to causal effects. Some of the major areas of criticism have to do with: (a) lack of a no-cause baseline, (b) spurious effects of mediating variables, and (c) obscuring effects of heterogeneous stabilities. The present author attempts to show that while these criticisms are valid, CLC should not be rejected outright as a tool in social science research. CLC has some utility as an exploratory technique. Furthermore, if certain assumptions are specified and these assumptions are correct, valid inferences can be made from CLC. Lastly, some assumptions for CLC are not as stringent as implied by critics and CLC is robust to minor violations of assumptions.

Educational and Psychological Measurement, Vol. 42, No. 4, 1023-1036 (1982)
DOI: 10.1177/001316448204200409


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