Imputation for estimating the population mean in the presence of nonresponse, with application to fine particle density in Bangkok

Abstract

ABSTRACT Air pollution in Bangkok, Thailand, is mainly due to fine particles emitted in exhaust gases. However, many data on fine particle concentrations are missing, a fact which may bias the statistics. Exponential-type imputation minimizing the mean square error allows for estimating the missing values of these concentrations and provides an estimate with smaller mean square error of the mean concentration levels. The bias and mean square error of the proposed estimator are calculated. Simulation shows that the relative efficiency is 5% higher up to 50 observations, 12% higher for 100 observations, and 25% higher for 200 observations. Application to the measurement of fine particle concentration in Bangkok yields a mean square error of 0.73 micrograms per cubic meter squared, for a mean level of 47.40 micrograms per cubic meter, while the mean square error by the best alternative estimator selected is 0.90 micrograms per cubic meter squared, for a mean level of 48.20 micrograms per cubic meter.