LEADER 04394nam 22005775 450 001 9910300105703321 005 20200630050941.0 010 $a3-319-98926-X 024 7 $a10.1007/978-3-319-98926-6 035 $a(CKB)4100000007111066 035 $a(MiAaPQ)EBC5592882 035 $a(DE-He213)978-3-319-98926-6 035 $a(PPN)232473935 035 $a(EXLCZ)994100000007111066 100 $a20181102d2018 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 14$aThe Measurement of Association$b[electronic resource] $eA Permutation Statistical Approach /$fby Kenneth J. Berry, Janis E. Johnston, Paul W. Mielke, Jr 205 $a1st ed. 2018. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2018. 215 $a1 online resource (647 pages) 311 $a3-319-98925-1 327 $a1 Introduction -- 2 Permutation Statistical Methods -- 3 Nominal Level Variables, I -- 4 Nominal Level Variables, II -- 5 Ordinal Level Variables, I -- 6 Ordinal Level Variables, II -- 7 Interval-level Variables -- 8 Mixed-level Variables -- 9 Fourfold Contingency Tables, I -- 10 Fourfold Contingency Tables, II -- Epilogue -- References -- Index. 330 $aThis research monograph utilizes exact and Monte Carlo permutation statistical methods to generate probability values and measures of effect size for a variety of measures of association. Association is broadly defined to include measures of correlation for two interval-level variables, measures of association for two nominal-level variables or two ordinal-level variables, and measures of agreement for two nominal-level or two ordinal-level variables. Additionally, measures of association for mixtures of the three levels of measurement are considered: nominal-ordinal, nominal-interval, and ordinal-interval measures. Numerous comparisons of permutation and classical statistical methods are presented. Unlike classical statistical methods, permutation statistical methods do not rely on theoretical distributions, avoid the usual assumptions of normality and homogeneity of variance, and depend only on the data at hand. This book takes a unique approach to explaining statistics by integrating a large variety of statistical methods, and establishing the rigor of a topic that to many may seem to be a nascent field. This topic is relatively new in that it took modern computing power to make permutation methods available to those working in mainstream research. Written for a statistically informed audience, it is particularly useful for teachers of statistics, practicing statisticians, applied statisticians, and quantitative graduate students in fields such as psychology, medical research, epidemiology, public health, and biology. It can also serve as a textbook in graduate courses in subjects like statistics, psychology, and biology. 606 $aStatistics  606 $aCombinatorics 606 $aBiostatistics 606 $aStatistical Theory and Methods$3https://scigraph.springernature.com/ontologies/product-market-codes/S11001 606 $aStatistics and Computing/Statistics Programs$3https://scigraph.springernature.com/ontologies/product-market-codes/S12008 606 $aStatistics for Life Sciences, Medicine, Health Sciences$3https://scigraph.springernature.com/ontologies/product-market-codes/S17030 606 $aCombinatorics$3https://scigraph.springernature.com/ontologies/product-market-codes/M29010 606 $aBiostatistics$3https://scigraph.springernature.com/ontologies/product-market-codes/L15020 615 0$aStatistics . 615 0$aCombinatorics. 615 0$aBiostatistics. 615 14$aStatistical Theory and Methods. 615 24$aStatistics and Computing/Statistics Programs. 615 24$aStatistics for Life Sciences, Medicine, Health Sciences. 615 24$aCombinatorics. 615 24$aBiostatistics. 676 $a519.5 700 $aBerry$b Kenneth J$4aut$4http://id.loc.gov/vocabulary/relators/aut$0148872 702 $aJohnston$b Janis E$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMielke$b Jr., Paul W$4aut$4http://id.loc.gov/vocabulary/relators/aut 906 $aBOOK 912 $a9910300105703321 996 $aThe Measurement of Association$92235885 997 $aUNINA