Using Weights to Estimate Population Parameters from Survey Records

by Daniel A. Relles

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Explains an inexpensive and convenient procedure for obtaining nearly unbiased estimates of a population parameter [y] from a biased sample with only a small loss in the efficiency of the estimates. The usual procedure prescribed by statistical theory is to regress survey response variable [y] on explanatory variables whose population means can be reliably estimated from sample selection records. Those means are then plugged into the regression prediction formula. The simpler procedure is based on weighted means of [y]. The weighted-means procedure is applied to HASE data with good results. Provided the weights (1) adequately reproduce the population means of important predictor variables for [y] and (2) yield estimates with acceptably small variances, the simpler procedure is recommended for wide use in estimating population parameters from survey research data.

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