An Evaluation of Model-Dependent and Probability-Sampling Inferences in Sample Surveys

Abstract

Abstract In this paper we are concerned with inferences from a sample survey to a finite population. We contrast inferences that are dependent on an assumed model with inferences based on the randomization induced by the sample selection plan. Randomization consistency for finite population estimators is defined and adopted as a requirement of probability sampling. A numerical example is examined to illustrate the dangers in the use of model-dependent estimators even when the model is apparently consonant with the sample data. The paper concludes with a summary of principles that we believe should guide the practitioner of sample surveys of finite populations. Key Words: Randomization inferenceFinite population samplingConsistencyBest estimatorRobustnessBias