Using adaptive weighted least squares to reduce the lengths of confidence intervals

The author proposes an adaptive method which produces confidence intervals that are often narrower than those obtained by the traditional procedures. The proposed methods use both a weighted least squares approach to reduce the length of the confidence interval and a permutation technique to insure that its coverage probability is near the nominal level. The author reports simulations comparing the adaptive intervals to the traditional ones for the difference between two population means, for the slope in a simple linear regression, and for the slope in a multiple linear regression having two correlated exogenous variables. He is led to recommend adaptive intervals for sample sizes superior to 40 when the error distribution is not known to be Gaussian.     

A Bayesian approach to non-parametric monotone function estimation

Summary.  The paper proposes two Bayesian approaches to non-parametric monotone function estimation. The first approach uses a hierarchical Bayes framework and a characterization of smooth monotone functions given by Ramsay that allows unconstrained estimation. The second approach uses a Bayesian regression spline model of Smith and Kohn with a mixture distribution of constrained normal distributions as the prior for the regression coefficients to ensure the monotonicity of the resulting function estimate. The small sample properties of the two function estimators across a range of functions are provided via simulation and compared with existing methods. Asymptotic results are also given that show that Bayesian methods provide consistent function estimators for a large class of smooth functions. An example is provided involving economic demand functions that illustrates the application of the constrained regression spline estimator in the context of a multiple-regression model where two functions are constrained to be monotone.     

Grey seals red in tooth and claw: how Darwin helps model their population

Grey seals in Britain are a conservation success, brought back from the brink of extinction by protection in the early 20th century. The public love them. Fishermen hate them. The resurgence of the grey guzzlers threatens their livelihood, they say. Len Thomas shows how Charles Darwin's ideas are used to determine seal numbers and population dynamics. Surprisingly, Darwin's theories have also influenced the statistical tools that are used.     

Semiparametric log-linear regression for longitudinal measurements subject to outcome-dependent follow-up

A common problem for longitudinal data analyses is that subjects follow-up is irregular, often related to the past outcome or other factors associated with the outcome measure that are not included in the regression model. Analyses unadjusted for outcome-dependent follow-up yield biased estimates. We propose a longitudinal data analysis that can provide consistent estimates in regression models that are subject to outcome-dependent follow-up. We focus on semiparametric marginal log-link regression with arbitrary unspecified baseline function. Based on estimating equations, the proposed class of estimators are root n consistent and asymptotically normal. We present simulation studies that assess the performance of the estimators under finite samples. We illustrate our approach using data from a health services research study.     

A value of information framework for assessing the trade-offs associated with uncertainty,duration, and cost of chemical toxicity testing

A number of investigators have explored the use of value of information (VOI) analysis to evaluate alternative information collection procedures in diverse decision-making contexts. This paper presents an analytic framework for determining the value of toxicity information used in risk-based decision making. The framework is specifically designed to explore the trade-offs between cost, timeliness, and uncertainty reduction associated with different toxicity-testing methodologies. The use of the proposed framework is demonstrated by two illustrative applications which, although based on simplified assumptions, show the insights that can be obtained through the use of VOI analysis. Specifically, these results suggest that timeliness of information collection has a significant impact on estimates of the VOI of chemical toxicity tests, even in the presence of smaller reductions in uncertainty. The framework introduces the concept of the expected value of delayed sample information, as an extension to the usual expected value of sample information, to accommodate the reductions in value resulting from delayed decision making. Our analysis also suggests that lower cost and higher throughput testing also may be beneficial in terms of public health benefits by increasing the number of substances that can be evaluated within a given budget. When the relative value is expressed in terms of return-on-investment per testing strategy, the differences can be substantial.     

Assessment of a State TANF Funded IDA Initiative: A Case Study

Individual development accounts (IDAs), wealth-building programs for the working poor, have existed since the late 1980s. Current research suggests that IDA programs benefit families while contributing to local and state economies. This program evaluation assessed the impact of one state Temporary Assistance for Needy Families (TANF)-funded IDA initiative. Quantitative and qualitative data were collected from four agencies chosen using cluster sampling across the state. Agency programmatic and participant data from the last year of operation (N?=?160) were examined. Agencies also provided contact information for three participants who had graduated and three who exited the program prematurely in the past year of operation. In person, interviews were held with agency directors (n?=?6) and IDA participants (n?=?11) were interviewed by telephone. Results indicate that 69% (n?=?111) of IDA enrollees successfully completed the program. IDA participants who exited the program prior to completion also expressed benefits associated with the time in which they were involved. Programmatic and individual benefits and challenges reported guide recommendations for improving IDA marketability, participant outcomes, and organizational performance rates. A critical implication of the findings is the need to expand the use and design of IDA programs legislatively to better serve historically oppressed and working poor families more effectively.     

Behavioral economics and the value of a statistical life

Journal of Risk and Uncertainty - There are many possible connections between the value of statistical life (VSL) and behavioral economics. A list of topics includes endowment effects, risk...