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Biomedical subjects

D M Zucker

Publications and source records attributed to D M Zucker.

8 recordsLinked to original sources
PubMed1995

Statistical design of the Child and Adolescent Trial for Cardiovascular Health (CATCH): implications of cluster randomization.

This paper describes some statistical considerations for the Child and Adolescent Trial for Cardiovascular Health (CATCH), a large-scale community health trial sponsored by the National Heart, Lung, and Blood Institute. The trial involves randomization of entire schools rather than individual students to the experimental arms. The paper discussed the implications of this form of randomization for the design and analysis of the trial. The power calculations and analysis plan for the trial are presented in detail. The handling of outmigrating and immigrating students is also discussed.

Adolescent↗
PubMed1995

Inference for the association between coefficients in a multivariate growth curve model.

This paper generalizes the work of Blomqvist (1977, Journal of the American Statistical Association 72, 746-749) on inference for the relationship between the individual-specific slope and the individual-specific intercept in a linear growth curve model. The paper deals with longitudinal data involving one or more response variables and irregular follow-up times, with each response variable postulated to follow a linear growth curve model. The problem considered is inference concerning the association between one growth curve coefficient and another--for example, the slope and intercept for a selected response variable, or the two slopes for two different response variables--after adjusting for all remaining coefficients among all of the response variables. An inferential approach based on the method of moments and an inferential approach based on maximum likelihood are described, and the asymptotic properties of these procedures are presented. Extensions of the methodology to allow polynomial growth curves and baseline covariates are outlined. The methodology is illustrated with a practical example arising from a clinical trial in lung disease.

Body Height↗
PubMed1992

The efficiency of a weighed log-rank test under a percent error misspecification model for the log hazard ratio.

For comparison of two survival distributions, it is natural to use a weighted log-rank test with weight function given by the log hazard ratio function that is anticipated a priori. This paper investigates the efficiency of this test when the a priori estimate of the log hazard ratio is subject to a specified percentage error. The test is shown to be the maximum efficiency robust test over the class of alternatives in question and a simple expression for the maximum efficiency is established.

Clinical Trials as Topic↗
PubMed1989

Research design and analysis issues.

The overall perspective of this article is the need for researchers of school-based health promotion to make more progressive use of existing statistical methods to improve both the rigor and the efficiency of school-based experiments. Investigative teams working in the school setting have an advantage over health education researchers working in communities or worksites in that they have greater choice of the experimental unit and usually easier access to large clusters of units. They are, therefore, in a position to make optimal use of a wide variety of experimental designs and observation strategies. In order to make full use of this advantage, however, researchers in this field need to assemble multidisciplinary teams, including researchers from other fields who are not restricted by the traditional approaches evident in many of the current school studies. Such teams should include statisticians and epidemiologists who have broadly-based experimental design and survey experience to work with the health educators and other behavioral and biomedical scientists.

Data Interpretation, Statistical↗
PubMed1989

Analysis issues in school-based health promotion studies.

In school-based research, usually the nature of the intervention or other practical factors indicate that assignment of treatment be done by school or classroom rather than by individual student. In this situation, randomization of schools (or classrooms) and analysis by school means (or classroom means) provide a firm statistical basis for internal validity of the study. When the number of schools available is small, this approach is not practicable, and therefore the investigator must be both more creative in developing solutions and more cautious in interpreting the results. This article provides a number of suggestions which the authors hope will assist the field in dealing with such circumstances. The authors stress that the best approach to assessing treatment effect is a well-designed, properly analyzed randomized experiment. The suggestions in this article attempt to indicate how one might make the most that one can from more limited data.

Data Interpretation, Statistical↗
PubMedDate not supplied

Studying the relationship between change and initial value in longitudinal studies.

Blomqvist's problem of studying the relationship between change and initial value in a linear growth curve setting is reformulated from a random effects model perspective. First, a maximum likelihood estimate of the between-individual covariance matrix for a simple linear regression model with stochastic parameters is obtained via an EM algorithm as discussed by Laird and Ware. Second, the regression coefficient of the individual-specific slopes on the individual-specific intercepts is estimated as a ratio of elements of the between-individual covariance matrix as discussed by Zucker et al. Then a Fieller's type confidence interval for this ratio is proposed. Discussion is facilitated by recognizing the Laird-Ware model as a special case of a more general model discussed by Hocking.

Algorithms↗