Permutation Methods [electronic resource] : A Distance Function Approach / by Paul W. Mielke, Kenneth J. Berry.
Contributor(s): Berry, Kenneth J [author.] | SpringerLink (Online service)Material type: TextSeries: Springer Series in Statistics: Publisher: New York, NY : Springer New York, 2007Edition: SecondDescription: XVIII, 446 p. online resourceContent type: text Media type: computer Carrier type: online resourceISBN: 9780387698137Subject(s): Mathematics | Public health | Data mining | Biometrics (Biology) | Probabilities | Statistics | Psychometrics | Mathematics | Probability Theory and Stochastic Processes | Statistical Theory and Methods | Biometrics | Data Mining and Knowledge Discovery | Psychometrics | Public HealthAdditional physical formats: Printed edition:: No titleDDC classification: 519.2 LOC classification: QA273.A1-274.9QA274-274.9Online resources: Click here to access online
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Description 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.
Most 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 Fisher’s continuous method for combining P-values that arise from small data sets, multiple dichotomous response analyses, problems regarding Fisher’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.