Profiting from correlations: Adjusted estimators for categorical data.

Niebuhr, Tobias; Trabs, Mathias

To take sample biases and skewness in the observations into account, practitioners frequently weight their observations according to some marginal distribution. The present paper demonstrates that such weighting can indeed improve the estimation. Studying contingency tables, estimators for marginal distributions are proposed under the assumption that another marginal is known. It is shown that the weighted estimators have a strictly smaller asymptotic variance whenever the two marginals are correlated. The finite sample performance is illustrated in a simulation study. As an application to traffic accident data the method allows for correcting a well‐known bias in the observed injury severity distribution.

MARGINAL distributions; TRAFFIC accidents; CONTINGENCY tables; MATHEMATICAL category theory; STATISTICAL weighting

Applied Stochastic Models in Business & Industry, 2019, Vol 35, Issue 4, p1090

1524-1904

Academic Journal

10.1002/asmb.2452