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Details

Autor(en) / Beteiligte
Titel
Permutation Methods : A Distance Function Approach [electronic resource]
Auflage
2nd ed. 2007
Ort / Verlag
New York, NY : Springer New York
Erscheinungsjahr
2007
Link zum Volltext
Beschreibungen/Notizen
  • Description based upon print version of record.
  • Includes bibliographical references (p. [393]-421) and indexes.
  • 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.
  • English
Sprache
Englisch
Identifikatoren
ISBN: 1-280-96012-4, 9786610960125, 0-387-69813-2
DOI: 10.1007/978-0-387-69813-7
OCLC-Nummer: 191449842
Titel-ID: 9925035202806463