Biomedical subjects

J Tayman

Publications and source records attributed to J Tayman.

5 recordsLinked to original sources

PubMed2000

A note on the measurement of accuracy for subnational demographic estimates.

Mean absolute percentage error (MAPE), the measure most often used for evaluating subnational demographic estimates, is not always valid. We describe guidelines for determining when MAPE is valid. Applying them to case study data, we find that MAPE understates accuracy because it is unduly influenced by outliers. To overcome this problem, we calculate a transformed MAPE (MAPE-T) using a modified Box-Cox method. Because MAPE-T is not in the same scale as the untransformed absolute percentage errors, we provide a procedure for calculating MAPE-R, a measure in the same scale as the original observations. We argue that MAPE-R is a more appropriate summary measure of average absolute percentage error when the guidelines indicate that MAPE is not valid.

Censuses↗

PubMed1996

On the utility of population forecasts.

Many customers demand population forecasts, particularly for small areas. Although the forecast evaluation literature is extensive, it is dominated by a focus on accuracy. We go beyond accuracy by examining the concept of forecast utility in an evaluation of a sample of 2,709 counties and census tracts. We find that forecasters provide "value-added" knowledge for areas experiencing rapid change or areas with relatively large populations. For other areas, reduced value is more common than added value. Our results suggest that new forecasting strategies and methods such as composite modeling may substantially improve forecast utility.

Bias↗

PubMed1994

Small area demographic forecasts.

The author reviews the literature on small area forecasting with a focus on the work of Robert Schmitt. He finds that "the accuracy of small area forecasts has not increased appreciably over the past four decades, despite methodological progress, increased knowledge gained from the evaluation of forecasts, and more widely available and rich data. A comment made by Schmitt 40 years ago is still largely true today, 'No method is yet known for forecasting the population of small urban areas with a high degree of accuracy'...."

Demography↗

PubMed1989

Postcensal estimates of household income distributions.

This article develops and evaluates a method for deriving postcensal estimates of household income distributions for counties. A modified lognormal probability curve is used as a model of income distribution. The function is closely related to the classical lognormal model, but it contains a nonlinear component in its derivation. Simulated postcensal estimates of household income distributions are compared with 1980 census data for the counties in California. The results indicate that the modified lognormal curve approximates observed income distributions well and produces reliable postcensal estimates for areas with a wide variety of median income levels and numbers of households.

Family↗

PubMed1982

Measuring temporal stability in regression models of population estimation.

This paper introduces an empirical indicator designed to measure the temporal stability of regression models used to produce subnational population estimates. Analusis of 67 counties in Florida centers on 1970 total population estimates generated from ratio-correlation and difference-correlation models. Comparisons are made between eight different regression specifications and employ a quantitative measure of relative estimate accuracy. The major findings of this study are that (a) variable measurement and type are important determinants of estimate accuracy, and (b) although temporal stability of the coefficients impacts estimation errors, the influence is not as pervasive as is suggested in the literature.

Demography↗