Hostname: page-component-5b777bbd6c-gtgcz Total loading time: 0 Render date: 2025-06-22T11:48:09.578Z Has data issue: false hasContentIssue false
  • English
  • Français

Two-Step Hierarchical Estimation: Beyond Regression Analysis

Published online by Cambridge University Press:  04 January 2017

Christopher H. Achen
Christopher H. Achen*
Affiliation:
Department of Politics, Princeton University, Princeton, NJ 08544. e-mail: achen@princeton.edu
Get access Rights & Permissions [Opens in a new window]

Abstract

Two-step estimators for hierarchical models can be constructed even when neither stage is a conventional linear regression model. For example, the first stage might consist of probit models, or duration models, or event count models. The second stage might be a nonlinear regression specification. This note sketches some of the considerations that arise in ensuring that two-step estimators are consistent in such cases.

Type
Research Article
Information
Political Analysis , Volume 13 , Issue 4: Special Issue on Multilevel Modeling for Large Clusters , Autumn 2005 , pp. 447 - 456
Copyright
Copyright © The Author 2005. Published by Oxford University Press on behalf of the Society for Political Methodology 

Access options

Get access to the full version of this content by using one of the access options below. (Log in options will check for institutional or personal access. Content may require purchase if you do not have access.)

Article purchase

Temporarily unavailable

References

Bartels, Larry M. 1996. “Pooling Disparate Observations.” American Journal of Political Science 40: 905–942.Google Scholar
Belsley, David A., Kuh, Edwin, and Welsch, Roy E. 1980. Regression Diagnostics New York: Wiley.Google Scholar
Borjas, George J., and Sueyoshi, Glenn T. 1994. “A Two-Stage Estimator for Probit Models with Structural Group Effects.” Journal of Econometrics 64: 165–182.Google Scholar
Bowers, Jake, and Drake, Katherine W. 2005. “EDA for HLM: Visualization When Probabilistic Inference Fails.” Political Analysis doi:10.1093/pan/mpi031.Google Scholar
Bryk, Anthony S., and Raudenbush, Stephen W. 2001. Hierarchical Linear Models, 2nd ed. Newbury Park, CA: Sage.Google Scholar
Duch, Raymond, and Stevenson, Randy. 2005. “Context and the Economic Vote: A Multi-Level Analysis.” Political Analysis doi:10.1093/pan/mpi028.CrossRefGoogle Scholar
Franzese, Robert J. Jr. 2005. “Empirical Strategies for Various Manifestations of Multilevel Data.” Political Analysis doi:10.1093/pan/mpi024.CrossRefGoogle Scholar
Gibbons, Robert D., and Hedeker, Donald. 1997. “Random Effects Probit and Logistic Regression Models for Three-Level Data.” Biometrics 53: 1527–1537.Google Scholar
Hanushek, Erik A. 1974. “Efficient Estimators for Regressing Regression Coefficients.” American Statistician 28: 66–67.Google Scholar
Huber, John D., Kernell, Georgia, and Leoni, Eduardo. 2005. “Institutional Context, Cognitive Resources and Partisan Attachments Across Democracies.” Political Analysis doi:10.1093/pan/mpi025.Google Scholar
Jusko, Karen Long. 2005. “A Two-Step Binary Response Model for Cross-National Public Opinion Data: A Research Note.” Presented at the Midwest Political Science Association National Conference, April 7–10, 2005, Chicago.Google Scholar
Jusko, Karen Long, and Shively, Phillips W. 2005. “A Two-Step Strategy for the Analysis of Cross-National Public Opinion Data.” Political Analysis doi:10.1093/pan/mpi030.Google Scholar
Kedar, Orit. 2005. “How Diffusion of Power in Parliaments Affects Voter Choice.” Political Analysis doi:10.1093/pan/mpi029.Google Scholar
Lewis, Jeffrey B., and Linzer, Drew A. 2005. “Estimating Regression Models in which the Dependent Variable Is Based on Estimates.” Political Analysis doi:10.1093/pan/mpi026.Google Scholar
Lindley, Dennis V., and Smith, A. F. M. 1972. “Bayes Estimates for the Linear Model.” Journal of the Royal Statistical Society, Series B 34: 1–41.Google Scholar
Saxonhouse, Gary R. 1976. “Estimated Parameters as Dependent Varibles.” American Economic Review 66: 178–183.Google Scholar
Saxonhouse, Gary R. 1977. “Regressions from Samples Having Different Characteristics.” Review of Economics and Statistics 59: 234–237.Google Scholar
Snijders, Tom A.B., and Bosker, Roel J. 1999. Multilevel Analysis. London: Sage.Google Scholar
Western, Bruce. 1998. “Causal Heterogeneity in Comparative Research.” American Journal of Political Science 42: 1233–1259.Google Scholar