An iterative estimating procedure for probit-type nonresponse models in surveys with call backs

Abstract

This work attempts to treat the negatives to respond in sample plans when several tries or call backs in the capture of individual data are assumed. We also maintain the assumption that the respondents supply all the variables of interest when they are captured although the retries are kept on, even after previous captures, for a predetermined number of tries, r, fixed only for estimating purposes. Supposing that the different retries or call backs are exerted with different capture intensities, the response probabilities, which may vary from one individual to another, are searched by probit models whose parameters are estimated using conditioned likelihoods evaluated on the respondents only (other models, derived from error distributions different from normal, could also be possible by approximating numerical techniques quite similar to the ones proposed here). We present a numerical estimating algorithm, quite easy to implement, which may be used when the recorded information about data captures includes at least marginal results. Finally, we include some encouraging empirical simulations whose purpose is centred in testing and evaluating the practical performance of the procedure.