0000000000846582

AUTHOR

Thorsten Dickhaus

0000-0003-3084-3036

showing 2 related works from this author

Multiplicity- and dependency-adjusted p-values for control of the family-wise error rate

2016

Abstract Under the multiple testing framework, we propose the multiplicity- and dependency-adjustment method (MADAM) which transforms test statistics into adjusted p -values for control of the family-wise error rate. For demonstration, we apply the MADAM to data from a genetic association study.

0301 basic medicineStatistics and ProbabilityWord error rateMultiplicity (mathematics)Familywise error rateMadam01 natural sciences010104 statistics & probability03 medical and health sciences030104 developmental biologyStatisticsMultiple comparisons problemŠidák correctionPer-comparison error rate0101 mathematicsStatistics Probability and UncertaintyMathematicsStatistical hypothesis testingStatistics & Probability Letters
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Combining multiple hypothesis testing with machine learning increases the statistical power of genome-wide association studies

2016

Mieth, Bettina et al.

0301 basic medicineStatistical methodsComputer scienceGenome-wide association studyMachine learningcomputer.software_genreGenome-wide association studiesStatistical powerArticle[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]Set (abstract data type)03 medical and health sciences[INFO.INFO-LG]Computer Science [cs]/Machine Learning [cs.LG][MATH.MATH-ST]Mathematics [math]/Statistics [math.ST]10007 Department of EconomicsStatistical significanceReplication (statistics)genomeStatistical hypothesis testingGenetic association1000 MultidisciplinaryMultidisciplinarybusiness.industryComputational scienceInstitut für Mathematik330 EconomicsSupport vector machine030104 developmental biologyMultiple comparisons problemwide association studiesstatistical methodsArtificial intelligencebusinesscomputer
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