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Journal Article

Survey Nonresponse Adjustments for Estimates of Means

Roderick J. A. Little
International Statistical Review / Revue Internationale de Statistique
Vol. 54, No. 2 (Aug., 1986), pp. 139-157
DOI: 10.2307/1403140
Stable URL: http://www.jstor.org/stable/1403140
Page Count: 19
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Survey Nonresponse Adjustments for Estimates of Means
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Abstract

Theoretical properties of nonresponse adjustments based on adjustment cells are studied, for estimates of means for the whole population and in subclasses that cut across adjustment cells. Three forms of adjustment are considered: weighting by the inverse response rate within cells, post-stratification on known population cell counts, and mean imputation within adjustment cells. Two dimensions of covariate information x are distinguished as particularly useful for reducing nonresponse bias: the response propensity p̂(x) and the conditional mean ŷ(x) of the outcome variable y given x. Weighting within adjustment cells based on p̂(x) controls bias, but not necessarily variance. Imputation within adjustment cells based on ŷ(x) controls bias and variance. Post-stratification yields some gains in efficiency for overall population means, and smaller gains for means in subclasses of the population. A simulation study similar to that of Holt & Smith (1979) is described which explores the mean squared error properties of the estimators. Finally, some modifications of response propensity weighting to control variance are suggested. /// L'estimation de moyennes de la population et de sous-populations pour une enquête soumise à nonréponse est discutée. Trois méthodes d'ajustement pour nonréponse sont comparés: le weighting, la post-stratification et l'imputation de moyennes en classes d'ajustement. Deux dimensions des covariates x sont distinguées pour la réduction du biais de nonréponse, la tendence de réponse p̂(x) et la moyenne conditionnelle E(yǀx) du variable y sujet à nonréponse. Les caractéristiques de méthodes qui font usage de ces dimensions pour la création de classes d'ajustement sont recherchées au moyen de théorie et de simulation.

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