Weighted-bootstrap alignment of explanatory variables

Date

2008

Authors

Hall, Peter
Leng, Xiaoyan
Muller, Hans-Georg

Journal Title

Journal ISSN

Volume Title

Publisher

Elsevier

Abstract

Adjustment for covariates is a time-honored tool in statistical analysis and is often implemented by including the covariates that one intends to adjust as additional predictors in a model. This adjustment often does not work well when the underlying model is misspecified. We consider here the situation where we compare a response between two groups. This response may depend on a covariate for which the distribution differs between the two groups one intends to compare. This creates the potential that observed differences are due to differences in covariate levels rather than "genuine" population differences that cannot be explained by covariate differences. We propose a bootstrap-based adjustment method. Bootstrap weights are constructed with the aim of aligning bootstrap-weighted empirical distributions of the covariate between the two groups. Generally, the proposed weighted-bootstrap algorithm can be used to align or match the values of an explanatory variable as closely as desired to those of a given target distribution. We illustrate the proposed bootstrap adjustment method in simulations and in the analysis of data on the fecundity of historical cohorts of French-Canadian women.

Description

Keywords

Keywords: Adjustment; Distribution function; French-Canadian women; Group comparison; Matching; Observational study; Odds ratio

Citation

Source

Journal of Statistical Planning and Inference

Type

Journal article

Book Title

Entity type

Access Statement

License Rights

DOI

10.1016/j.jspi.2007.06.032

Restricted until

2037-12-31