TY - BOOK
AU - Mielke,Paul W.
AU - Berry,Kenneth J.
ED - SpringerLink (Online service)
TI - Permutation Methods: A Distance Function Approach
T2 - Springer Series in Statistics,
SN - 9780387698137
AV - QA273.A1-274.9
U1 - 519.2 23
PY - 2007///
CY - New York, NY
PB - Springer New York
KW - Mathematics
KW - Public health
KW - Data mining
KW - Biometrics (Biology)
KW - Probabilities
KW - Statistics
KW - Psychometrics
KW - Probability Theory and Stochastic Processes
KW - Statistical Theory and Methods
KW - Biometrics
KW - Data Mining and Knowledge Discovery
KW - Public Health
N1 - 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
N2 - 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 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
UR - http://dx.doi.org/10.1007/978-0-387-69813-7
ER -