Estimating the costs of preventive interventions

The goal of this article is to improve the practice and reporting of cost estimates of prevention programs. It reviews the steps in estimating the costs of an intervention and the principles that should guide estimation. The authors then review prior efforts to estimate intervention costs using a sample of well-known but diverse studies. Finally, the authors illustrate the principles with an example, the Family Bereavement Program. They conclude that example by discussing whether and how the costs of the intervention might differ when implemented in a real-world setting.     

A Dynamic Model of Investment in the U.S. Beef-Cattle Industry

Reproduction constraints lead to some a priori information that may prove valuable in econo- metrically modeling inventory dynamics within the U.S. cattle herd. The distributed-lag models estimated for animal inventories suggest an implicit incorporation of the age distribution of the herd that is crucial to understanding the retention/culling (investment) decisions. The estimated equations are validated using post-sample observations that were withheld prior to estimation. The final-form dynamic equations have complex roots and protracted price and investment effects. The parameter estimates are used to calculate intermediate and long-run elasticities at the means of relevant variables.     

Estimation of Acute Toxicity by Fitting a Dose-Time-Response Surface

In acute toxicity testing, organisms are continuously exposed to progressively increasing concentrations of a chemical and deaths of test organisms are recorded at several selected times. The results of the test are traditionally summarized by a dose-response curve, and the time course of effect is usually ignored for lack of a suitable model. A model which integrates the combined effects of dose and exposure duration on response is derived from the biological mechanisms of aquatic toxicity, and a statistically efficient approach for estimating acute toxicity by fitting the proposed model is developed in this paper. The proposed procedure has been computerized as software and a typical data set is used to illustrate the theory and procedure. The new statistical technique is also tested by a data base of a variety of chemical and fish species.     

Are Cohort Mortality Rates Autocorrelated?

In this paper the author examines the proposition that heterogeneity in individual frailty leads to autocorrelation in cohort mortality rates. A simple model is used to construct analytic expressions for the covariance of cohort mortality rates at different ages under a number of alternative assumptions about the stochastic process generating shocks in mortality. The model then is used to construct a procedure that uses correlations in cohort mortality rates to estimate the extent of heterogeneity in a population without relying on strong assumptions about the distribution of frailty or the shape of the underlying hazard. The procedure then is used to show that cohort mortality data from France are consistent with a generalized random-effects model in which frailty is gamma-distributed.