Titlebook: Statistics Applied to Clinical Trials; Ton J. Cleophas,Aeilko H. Zwinderman,Toine F. Cleo Book 20063rd edition Springer Science+Business M

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The Interpretation of the P-Values,ting-the-errors / maintaining-the-outliers. Statistical tests are, traditionally, not very good at distinguishing between errors and outliers. However, they should be able to point out main endpoint results that are closer to expectation than compatible with random sampling. E.g., a difference from

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Research Data Closer to Expectation than Compatible with Random Sampling,balanced random sampling of representative experimental data, nature will be helpful to provide researchers with results close to perfection. However, because biological processes are full of variations, nature will never allow for 100% perfection. Statistical distributions can account for this lack

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Subgroup Analysis Using Multiple Linear Regression: Confounding, Interaction, Synergism,efficacy responses; e.g. comparison of effects by age, sex; by severity or prognostic groups. Naturally, such analyses are not intended to “salvage” an otherwise negative study, but may be may be helpful in refining patient or dose selection for subsequent studies.

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Logistic and Cox Regression, Problems with Regression Modeling, Markow Models, on this topic have recently been published.. Although multiple regression modeling, generally, does not influence the magnitude of the treatment effect versus control, it may reduce overall variances in the treatment comparison and thus increase sensitivity or power of statistical testing. It tries

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Post-Hoc Analyses in Clinical Trials, a Case for Logistic Regression Analysis,rials simple primary hypotheses in terms of efficacy and safety expectations, are tested through their respective outcome variables as described in the protocol. However, sometimes it is decided already at the design stage that post hoc analyses will be performed for the purpose of testing secondary

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Interaction Effects in Clinical Trials,co-determine the efficacy of the new treatment. In statistical terms we say they interact with the treatment efficacy. It is impossible to estimate all of these factors. Instead, randomized controlled trials are used to ensure that no major inbalances exist regarding these factors, and an overall as