A Model-Based Look at Linear Regression with Survey Data
- 1 May 1991
- journal article
- research article
- Published by Taylor & Francis in The American Statistician
- Vol. 45 (2) , 107-112
- https://doi.org/10.1080/00031305.1991.10475779
Abstract
This article explores the ramifications of performing a linear regression on data obtained from a complex sample survey. The incorporation of sampling weights into estimated regression coefficients helps protect against the potential existence of missing regressors. In addition, the linearization variance estimator, computed by certain software regression packages designed specifically for use with survey data (e.g., SURREGR, SUPER CARP, and PC CARP), is robust against the likelihood of correlated errors and the possibility of heteroscedasticity.Keywords
This publication has 10 references indexed in Scilit:
- Estimating the conditional variance of a design consistent regression estimatorJournal of Statistical Planning and Inference, 1990
- Some asymptotic results for the systematic and stratified sampling of a finite populationBiometrika, 1986
- Robustness Considerations in the Choice of a Method of Inference for Regression Analysis of Survey DataJournal of the Royal Statistical Society. Series A (General), 1985
- On the Variances of Asymptotically Normal Estimators from Complex SurveysInternational Statistical Review, 1983
- An Evaluation of Model-Dependent and Probability-Sampling Inferences in Sample SurveysJournal of the American Statistical Association, 1983
- Using Sample Survey Weights in Multiple Regression Analyses of Stratified SamplesJournal of the American Statistical Association, 1983
- Regression Analysis of Data from Complex SurveysJournal of the Royal Statistical Society. Series A (General), 1980
- THE EFFECT OF SAMPLE STRUCTURE ON ANALYTICAL SURVEYS1,2Australian Journal of Statistics, 1973
- A Note on Error Components ModelsEconometrica, 1971
- On the Two Different Aspects of the Representative Method: The Method of Stratified Sampling and the Method of Purposive SelectionJournal of the Royal Statistical Society, 1934