Power of tests for a dichotomous independent variable measured with error.

ABSTRACT:

Objective

To examine the implications for statistical power of using predicted probabilities for a dichotomous independent variable, rather than the actual variable.

Data sources/study setting

An application uses 271,479 observations from the 2000 to 2002 CAHPS Medicare Fee-for-Service surveys. STUDY DESIGN AND DATA: A methodological study with simulation results and a substantive application to previously collected data.

Principle findings

Researchers often must employ key dichotomous predictors that are unobserved but for which predictions exist. We consider three approaches to such data: the classification estimator (1); the direct substitution estimator (2); the partial information maximum likelihood estimator (3, PIMLE). The efficiency of (1) (its power relative

SUBMITTER: McCaffrey DF 

PROVIDER: S-EPMC2442236 | biostudies-literature | 2008 Jun

REPOSITORIES: biostudies-literature