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Full-Text Articles in Physical Sciences and Mathematics

P-Values Versus Significance Levels, Phillip I. Good May 2013

P-Values Versus Significance Levels, Phillip I. Good

Journal of Modern Applied Statistical Methods

In this article Phillip Good responds to Richard Anderson's article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.


Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments, Richard B. Anderson May 2013

Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing: Author Response To Peer Comments, Richard B. Anderson

Journal of Modern Applied Statistical Methods

Richard Anderson responds to comments regarding his target article Conceptual Distinction between the Critical p Value and the Type I Error Rate in Permutation Testing.


A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini May 2013

A Response To Anderson's (2013) Conceptual Distinction Between The Critical P Value And Type I Error Rate In Permutation Testing, Fortunato Pesarin, Stefano Bonnini

Journal of Modern Applied Statistical Methods

Pesarin and Bonnini respond to Anderson's (2013) Conceptual Distinction between the Critical p value and Type I Error Rate in Permutation Testing


Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson May 2013

Conceptual Distinction Between The Critical P Value And The Type I Error Rate In Permutation Testing, Richard B. Anderson

Journal of Modern Applied Statistical Methods

To counter past assertions that permutation testing is not distribution-free, this article clarifies that the critical p value (alpha) in permutation testing is not a Type I error rate and that a test's validity is independent of the concept of Type I error.


Randomization Technique, Allocation Concealment, Masking, And Susceptibility Of Trials To Selection Bias, Vance W. Berger, Costas A. Christophi May 2003

Randomization Technique, Allocation Concealment, Masking, And Susceptibility Of Trials To Selection Bias, Vance W. Berger, Costas A. Christophi

Journal of Modern Applied Statistical Methods

It is widely believed that baseline imbalances in randomized clinical trials must necessarily be random. Yet even among masked randomized trials conducted with allocation concealment, there are mechanisms by which patients with specific covariates may be selected for inclusion into a particular treatment group. This selection bias would force imbalance in those covariates, measured or unmeasured, that are used for the patient selection. Unfortunately, few trials provide adequate information to determine even if there was allocation concealment, how the randomization was conducted, and how successful the masking may have been, let alone if selection bias was adequately controlle d. In …


Parametric Analyses In Randomized Clinical Trials, Vance W. Berger, Clifford E. Lunneborg, Michael D. Ernst, Jonathan G. Levine May 2002

Parametric Analyses In Randomized Clinical Trials, Vance W. Berger, Clifford E. Lunneborg, Michael D. Ernst, Jonathan G. Levine

Journal of Modern Applied Statistical Methods

One salient feature of randomized clinical trials is that patients are randomly allocated to treatment groups, but not randomly sampled from any target population. Without random sampling parametric analyses are inexact, yet they are still often used in clinical trials. Given the availability of an exact test, it would still be conceivable to argue convincingly that for technical reasons (upon which we elaborate) a parametric test might be preferable in some situations. Having acknowledged this possibility, we point out that such an argument cannot be convincing without supporting facts concerning the specifics of the problem at hand. Moreover, we have …