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In a long term clinical trial to evaluate a new treatment, quite often each study subject may experience a number of 'failures' that correspond to repeated occurrences of the same type of event or events of entirely different natures during his/her follow-up period. To obtain efficient inference procedures for the therapeutic effect over time, it is(More)
We present methods for the analysis of a K-variate binary measure for two independent groups where some observations may be incomplete, as in the case of K repeated measures in a comparative trial. For the K 2 X 2 tables, let theta = (theta 1,..., theta K) be a vector of association parameters where theta k is a measure of association that is a continuous(More)
In this article we review the important statistical properties of the urn randomization (design) for assigning patients to treatment groups in a clinical trial. The urn design is the most widely studied member of the family of adaptive biased-coin designs. Such designs are a compromise between designs that yield perfect balance in treatment assignments and(More)
The statistical properties of simple (complete) randomization, permuted-block (or simply blocked) randomization, and the urn adaptive biased-coin randomization are summarized. These procedures are contrasted to covariate adaptive procedures such as minimization and to response adaptive procedures such as the play-the-winner rule. General recommendations are(More)
When comparing a new treatment with a control in a randomized clinical study, the treatment effect is generally assessed by evaluating a summary measure over a specific study population. The success of the trial heavily depends on the choice of such a population. In this paper, we show a systematic, effective way to identify a promising population, for(More)
Suppose that subjects are observed repeatedly over a common set of time points with possibly time-dependent covariates and possibly missing observations. At each time point we model the marginal distribution of the response variable and the effect of the covariates on that distribution using a class of quasi-likelihood models studied in McCullagh and(More)
To estimate an overall treatment difference with data from a randomized comparative clinical study, baseline covariates are often utilized to increase the estimation precision. Using the standard analysis of covariance technique for making inferences about such an average treatment difference may not be appropriate, especially when the fitted model is(More)
Online publish-ahead-of-print 17 January 2013 This editorial refers to 'Evaluation of early percutaneous coronary intervention vs. standard therapy after fibrinoly-sis for ST-segment elevation myocardial infarction: contribution of weighting the composite endpoint' † , by J.A. The randomized controlled clinical trial currently represents the gold standard(More)
In comparing the effectiveness of two treatments, suppose that nondecreasing repeated measurements of the same characteristic are scheduled to be taken over a common set of time points for each study subject. A class of univariate one-sided global asymptotically distribution-free tests is proposed to test the equality of the two treatments. The test(More)
In a longitudinal study, suppose that the primary endpoint is the time to a specific event. This response variable, however, may be censored by an independent censoring variable or by the occurrence of one of several dependent competing events. For each study subject, a set of baseline covariates is collected. The question is how to construct a reliable(More)