# Download Analysis of Clinical Trials Using SAS: A Practical Guide by Alex Dmitrienko PDF

By Alex Dmitrienko

In research of scientific Trials utilizing SAS: a pragmatic consultant, Alex Dmitrienko, Geert Molenberghs, Christy Chuang-Stein, and Walter Offen bridge the space among smooth statistical technique and real-world scientific trial purposes. step by step directions illustrated with examples from genuine trials and case experiences serve to outline a statistical strategy and its relevance in a medical trials atmosphere and to demonstrate the right way to enforce the tactic speedily and successfully utilizing the ability of SAS software program. issues mirror the foreign convention on Harmonization (ICH) directions for the pharmaceutical and deal with vital statistical difficulties encountered in scientific trials, together with research of stratified facts, incomplete info, a number of inferences, concerns coming up in security and efficacy tracking, and reference durations for severe safeguard and diagnostic measurements. medical statisticians, learn scientists, and graduate scholars in biostatistics will significantly enjoy the a long time of scientific examine event compiled during this e-book. a variety of ready-to-use SAS macros and instance code are integrated.

This ebook is a part of the SAS Press application.

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Extra info for Analysis of Clinical Trials Using SAS: A Practical Guide

Example text

Radhakrishna (1965) provided a detailed analysis of stratiﬁed tests and demonstrated that the weighting strategy used in the CMH procedure works best (in terms of the power to detect a treatment difference) when odds ratios of an event of interest are constant across strata. This weighting strategy (known as the SSIZE strategy) may not be very effective when this assumption is not met. This happens, for example, when a constant multiplicative or constant additive treatment effect is observed (in other words, strata are homogeneous with respect to the relative risk or risk difference).

In other words, the CMH statistic follows a chi-square distribution even in the presence of a large number of small strata. Mantel and Fleiss (1980) studied the accuracy of the chi-square approximation and devised a simple rule to conﬁrm the adequacy of this approximation in practice. It is appropriate to compute the CMH p-value from a chi-square distribution with 1 degree of freedom if both m i=1 m n 1i+ n +i1 − max(0, n +i1 − n 2i+ ) ni min(n 1i+ , n +i1 ) − and i=1 n 1i+ n +i1 ni exceed 5. 4) or Koch and Edwards (1988) for more details.

However, random effects inferences are generally less powerful than inferences based on ﬁxed effects models. This is one of the reasons why stratiﬁed analyses based on random effects models are rarely performed in a clinical trial setting. A stratiﬁed version of the nonparametric Wilcoxon rank-sum test, known as the van Elteren test, can be used to perform inferences in a non-normal setting. It has been shown that the asymptotic distribution of the van Elteren test statistic is not directly affected by the size of individual strata and therefore this testing procedure performs well in the analysis of a large number of small strata.