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Biomedical subjects

M R Selwyn

Publications and source records attributed to M R Selwyn.

6 recordsLinked to original sources

The application of large Gaussian mixed models to the analysis of 24 hour ambulatory blood pressure monitoring data in clinical trials.

We propose the use of Gaussian mixed models to analyse statistically 24 hour ambulatory blood pressure data from clinical trials. We develop specific models and apply them to data from a clinical study that compares two angiotensin-converting enzyme inhibitors. We investigate and discuss computing issues related to the implementation of such methods. We conclude that this methodology provides a sophisticated but practical approach to the analysis of such data.

Adult

Dual controls, p-value plots, and the multiple testing issue in carcinogenicity studies.

The interpretation of statistically significant findings in a carcinogenicity study is difficult, in part because of the large number of statistical tests conducted. Some scientists who believe that the false positive rates in these experiments are unreasonably large often suggest that the use of multiple control groups will provide important insight into the operational false positive rates. The purpose of this paper is 2-fold: to present results from two carcinogenicity studies with dual control groups, and to present and illustrate a new graphical technique potentially useful in the analysis and interpretation of tumor data from carcinogenicity studies. The experimental data analyzed show that statistically significant differences between identically treated groups will occur with regular frequency. Such data, however, do not provide strong evidence of extrabinomial variation in tumor rates. The p-value plot is advocated as a graphical method that can be used to assess visually the ensemble of p values for neoplasm data from an entire study. This technique is then illustrated using several examples. Through computer simulation, we present p-value plots generated with and without treatment effects present. On average, the plots look substantially different depending on the presence or absence of an effect. We also evaluate decision rules motivated by the p-value plots. Such rules appear to have good power to detect treatment effects (i.e., have low false negative rates) while still controlling false positive rates.

Animals

On Bayesian methods for bioequivalence.

Bayesian methods are presented for assessing bioequivalence for studies in which a new formulation and a standard are administered simultaneously, and for Latin square designs which compare two or more new formulations to a standard. Two examples illustrate the application of the methods.

Biometry

A Bayesian approach to bioequivalence for the 2 x 2 changeover design.

Bioequivalence trials are carried out to compare two or more formulations of a drug containing the same active ingredient, in order to determine whether the different formulation give rise to comparable blood levels. We consider the 2 x 2 changeover experiment the compares two formulations, one of which is considered the standard. For a single univariate characteristic of the plasma concentration--time curve, a criterion for bioequivalence is proposed based on the posterior probability that the difference in formulation means is less than a specific percentage of the mean of the standard. The sensitivity of this posterior probability to alternative priors is investigated. Differences in carry-over effects can be incorporated within the Bayesian framework without restoring to the "all-or-nothing" approach implied by a preliminary test. The use of sequential experimentation is discussed.

Bayes Theorem