Biomedical subjects

D O Scharfstein

Publications and source records attributed to D O Scharfstein.

5 recordsLinked to original sources

PubMed2001

The quadratic cumulative odds regression model for scored ordinal outcomes: application to alcohol dependence.

In this paper, we develop new regression models for the analysis of scored ordinal data (i.e. ordinal outcomes where the categories are assigned numeric values). The novel feature of these models is that they enable one to capture and identify nonlinear aspects of the relationship between an ordinal clinical measurement (used for disease diagnosis) and risk factors. These nonlinearities may be useful in generating hypotheses about the risk factor's role in the etiologic process as well as suggesting how to design future studies of the risk factor. We apply our model to study the effects of race, gender, and family history on alcohol dependence among a cohort of lifetime drinkers from the 1992 National Longitudinal Alcohol Epidemiologic Survey.

Journal Article↗

PubMed1998

The use of simulation and bootstrap in information-based group sequential studies.

In this paper, we present an information-based design and monitoring procedure which applies to any type of model for any type of group sequential study provided there is a unique parameter of interest one can estimate efficiently. Simulation techniques are described to handle the design phase of this procedure. Since designs depend on potentially unreliable guesses of nuisance parameters, we propose a bootstrap method that uses the information available at the interim analysis times to generate projections and prediction intervals for the time at which the study will be fully powered. A monitoring board can use this information to decide whether a redesign of the trial is warranted. We also show how to use simulation to redesign studies in progress. We illustrate all of these techniques with data from AIDS Clinical Trial Group Protocol 021.

AIDS-Related Opportunistic Infections↗

PubMed1998

Semiparametric efficient estimation in the generalized odds-rate class of regression models for right-censored time-to-event data.

The generalized odds-rate class of regression models for time to event data is indexed by a non-negative constant rho and assumes that [formula: see text] where g: rho(s) = log(rho-1(s-rho - 1)) for rho > 0, g0(s) = log(-logs), S(t[symbol: see text]Z) is the survival function of the time to event for an individual with q x 1 covariate vector Z, beta is a q x 1 vector of unknown regression parameters, and alpha(t) is some arbitrary increasing function of t. When rho = 0, this model is equivalent to the proportional hazards model and when rho = 1, this model reduces to the proportional odds model. In the presence of right censoring, we construct estimators for beta and exp(alpha(t)) and show that they are consistent and asymptotically normal. In addition, we show that the estimator for beta is semiparametric efficient in the sense that it attains the semiparametric variance bound.

Biometry↗

PubMed1994

Design of developmental toxicity studies for assessing joint effects of dose and duration.

In the assessment of developmental and reproductive effects, the timing and duration of exposures to chemical compounds or other environmental contaminants are of particular interest, as the gestational cycle is known to have periods of increased sensitivity. The goal of this research is to identify optimal experimental designs for conducting developmental toxicity studies when the effects of both exposure level and duration of exposure are of interest. The elements of the study design considered in this evaluation are the allocation of animals to dose-duration exposure groups and the determination of the most efficient intermediate exposure levels. The optimality of various designs is assessed via the accuracy of the estimated excess risk as well as testing criteria. Simulation studies are conducted to compare these criteria and determine optimal design strategies under various underlying dose-response patterns. Asymptotic results are also derived to lend support to the simulation studies.

Abnormalities, Drug-Induced↗

PubMed1993

Statistical model for fetal death, fetal weight, and malformation in developmental toxicity studies.

The purpose of this paper is to present a statistical model for analyzing the joint effects of exposure on fetal death, fetal weight, and malformation in a developmental toxicity study. In addition to allowing for the usual litter effect, the model allows for correlations between different outcomes measured on the same fetus. Fitting the model requires first focusing on non-live outcomes by modeling the probability of fetal death or resorption as a function of dose. Then outcomes among live fetuses are modeled using a two-stage regression approach. The first stage models fetal weight as a function of dose and the second stage models fetal malformation as a function of dose, as well as residuals from the weight model. The regression coefficients from the malformation model have intuitive interpretations in terms of correlations between littermates and between different outcomes measured within the same fetus. Not only does the approach provide a useful way to investigate the relationship between adverse fetal outcomes, it also yields a natural framework for conducting quantitative risk assessment. A procedure is proposed for quantifying overall risk by incorporating the three outcomes in order to estimate safe dose levels and corresponding lower confidence limits. The method is illustrated using data from an experiment in mice conducted through the National Toxicology Program.

Abnormalities, Drug-Induced↗