Literature DB >> 2364136

A modified Bonferroni method for discrete data.

R E Tarone1.   

Abstract

The Bonferroni adjustment for multiple comparisons is a simple and useful method of controlling the overall false positive error rate when several significance tests are performed in the evaluation of an experiment. In situations with categorical data, the test statistics have discrete distributions. The discreteness of the null distributions can be exploited to reduce the number of significance tests taken into account in the Bonferroni procedure. This reduction is accomplished by using only the information contained in the marginal totals.

Mesh:

Year:  1990        PMID: 2364136

Source DB:  PubMed          Journal:  Biometrics        ISSN: 0006-341X            Impact factor:   2.571


  49 in total

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2.  Statistical significance of combinatorial regulations.

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4.  Randomised P-values and nonparametric procedures in multiple testing.

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5.  Estimating the proportion of true null hypotheses when the statistics are discrete.

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6.  Common genetic variants in metabolism and detoxification pathways and the risk of papillary thyroid cancer.

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7.  Comprehensive Evaluation of Medical Conditions Associated with Risk of Non-Hodgkin Lymphoma using Medicare Claims ("MedWAS").

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8.  Association of CAV1/CAV2 genomic variants with primary open-angle glaucoma overall and by gender and pattern of visual field loss.

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Journal:  Ophthalmology       Date:  2013-10-25       Impact factor: 12.079

9.  H2S ameliorates oxidative and proteolytic stresses and protects the heart against adverse remodeling in chronic heart failure.

Authors:  Paras K Mishra; Neetu Tyagi; Utpal Sen; Srikanth Givvimani; Suresh C Tyagi
Journal:  Am J Physiol Heart Circ Physiol       Date:  2009-11-20       Impact factor: 4.733

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Journal:  Am J Physiol Endocrinol Metab       Date:  2008-09-09       Impact factor: 4.310

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