INDIRECT SAMPLING in the CONTEXT of DUAL FRAME SURVEYS

Under-coverage is one of the most common problems of sampling frames. To reduce the impact of coverage error on survey estimates several frames can be combined in order to achieve a complete (or nearly complete) coverage of the target population. Multiple frame estimators have been developed to be used in the context of multiple frame surveys. Sampling frames may overlap which is the case when a single unit of the sampling frame is related with more than one element of the target population. Indirect sampling (Lavallée, 1995) is an alternative approach to classical sampling theory in dealing with the overlapping problem of sampling frames on survey estimates. Not infrequently a survey may need more than one sampling frame in order to improve coverage and simultaneously the sampling frame overlap. In this paper a new class of estimators is presented which is the result from merging multiple frames estimators (only the particular case of dual frames will be presented) with indirect sampling estimators in order to bring together in a single estimator the effect of several frames on survey estimates.