The probabilistic analysis of testimony

The probabilistic analysis of testimony is surveyed. The coverage is not comprehensive; attention is focused on several problems of particular interest or complexity. The theory often contains implicit assumptions, and some attempt is made to clarify the role these play. The theory originally arose in an attempt to understand the logic of belief. It was not empirically grounded, however, and later died out in the 19th century when its conclusions became largely self-evident, and its non-empirical background suspect.     

Determinants of fertility levels and change among developed countries: 1958–1978

This article provides a multivariate cross-national test of the hypothesis that national population/family planning policies have effected levels, and changes in fertility in developed nations over the past two decades. Variation is assessed in the total fertility rates (TFR) in 1978, and in the change in these rates between 1958 and 1978, among thirty developed countries. Measures include socioeconomic development, divorce, percent in consensual unions, female labor force participation, abortion policy, and level of contraceptive use by married couples and, government population/family planning policy. Seventy percent of the variation in 1978 TFR is related to the percent contracepting, female labor force, and the population/family planning policy measures. These are the only measures with significant direct effects. A longitudinal analysis of 1958 to 1978 change in TFRs is also conducted. This model increases R² to 75%, and the three independent variables remain significant. Implications of these findings for policy makers interested in increasing or decreasing fertility rates are noted.     

ESTIMATING THE PARAMETERS OF NORMAL AND LOGISTIC DISTRIBUTIONS FROM CENSORED SAMPLES1

Let g(z) be the ratio of the ordinate and the probability integral of the distribution of a variate z. The relation g(z)～+βz is used to derive (i) estimators μ_r and s?_r of the parameters of a truncated normal distribution and (ii) estimators μ_c and s?_c of the mean and standard deviation of a logistic distribution from doubly censored samples. The variances and eovariances of these estimators are obtained. They are shown to be nearly as efficient as the maximum likelihood estimators and easier to compute.