03383nam a22005655i 4500001001800000003000900018005001700027007001500044008004100059020001800100024003500118050001900153050001600172072001600188072001700204072002300221082001400244100002900258245011900287250001200406264004600418300003600464336002600500337002600526338003600552347002400588490004600612505024200658520137200900650001702272650001902289650001702308650002602325650001902351650001602370650001902386650001702405650004902422650003602471650001602507650004102523650001902564650001902583700003102602710003402633773002002667776003602687830004602723856004802769978-0-387-69813-7DE-He21320180115171412.0cr nn 008mamaa100301s2007 xxu| s |||| 0|eng d a97803876981377 a10.1007/978-0-387-69813-72doi 4aQA273.A1-274.9 4aQA274-274.9 7aPBT2bicssc 7aPBWL2bicssc 7aMAT0290002bisacsh04a519.22231 aMielke, Paul W.eauthor.10aPermutation Methodsh[electronic resource] :bA Distance Function Approach /cby Paul W. Mielke, Kenneth J. Berry. aSecond. 1aNew York, NY :bSpringer New York,c2007. aXVIII, 446 p.bonline resource. atextbtxt2rdacontent acomputerbc2rdamedia aonline resourcebcr2rdacarrier atext filebPDF2rda1 aSpringer Series in Statistics,x0172-73970 aDescription of MRPP -- Additional MRPP Applications -- Description of MRBP -- Regression Analysis, Prediction, and Agreement -- Goodness-of-Fit Tests -- Contingency Tables -- Multisample Homogeneity Tests -- Selected Permutation Studies. aMost commonly-used parametric and permutation statistical tests, such as the matched-pairs t test and analysis of variance, are based on non-metric squared distance functions that have very poor robustness characteristics. This second edition places increased emphasis on the use of alternative permutation statistical tests based on metric Euclidean distance functions that have excellent robustness characteristics. These alternative permutation techniques provide many powerful multivariate tests including multivariate multiple regression analyses. In addition to permutation techniques described in the first edition, this second edition also contains various new permutation statistical methods and studies that include resampling multiple contingency table analyses, analysis concerns involving log-linear models with small samples, an exact discrete analog of Fisherâ€™s continuous method for combining P-values that arise from small data sets, multiple dichotomous response analyses, problems regarding Fisherâ€™s Z transformation for correlation analyses, and multivariate similarity comparisons between corresponding multiple categories of two samples. Paul W. Mielke, Jr. is Professor of Statistics at Colorado State University, and a fellow of the American Statistical Association. Kenneth J. Berry is Professor of Sociology at Colorado State University. 0aMathematics. 0aPublic health. 0aData mining. 0aBiometrics (Biology). 0aProbabilities. 0aStatistics. 0aPsychometrics.14aMathematics.24aProbability Theory and Stochastic Processes.24aStatistical Theory and Methods.24aBiometrics.24aData Mining and Knowledge Discovery.24aPsychometrics.24aPublic Health.1 aBerry, Kenneth J.eauthor.2 aSpringerLink (Online service)0 tSpringer eBooks08iPrinted edition:z9780387698113 0aSpringer Series in Statistics,x0172-739740uhttp://dx.doi.org/10.1007/978-0-387-69813-7