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010   $a9783319989266
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024 7 $a10.1007/978-3-319-98926-6
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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 $eA Permutation Statistical Approach /$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   $a1 online resource (647 pages)
311 08$a9783319989259 
311 08$a3319989251 
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   $aMathematical statistics$xData processing
606   $aBiometry
606   $aDiscrete mathematics
606   $aStatistical Theory and Methods
606   $aStatistics and Computing
606   $aBiostatistics
606   $aDiscrete Mathematics
615  0$aStatistics.
615  0$aMathematical statistics$xData processing.
615  0$aBiometry.
615  0$aDiscrete mathematics.
615 14$aStatistical Theory and Methods.
615 24$aStatistics and Computing.
615 24$aBiostatistics.
615 24$aDiscrete Mathematics.
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