LEADER 04372nam 22006615 450 001 9910350243403321 005 20250331003726.0 010 $a9789811500664 010 $a9811500665 024 7 $a10.1007/978-981-15-0066-4 035 $a(CKB)4100000009757407 035 $a(MiAaPQ)EBC5916270 035 $a(DE-He213)978-981-15-0066-4 035 $a(PPN)258305061 035 $a(EXLCZ)994100000009757407 100 $a20190930d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aPairwise Multiple Comparisons $eTheory and Computation /$fby Taka-aki Shiraishi, Hiroshi Sugiura, Shin-ichi Matsuda 205 $a1st ed. 2019. 210 1$aSingapore :$cSpringer Nature Singapore :$cImprint: Springer,$d2019. 215 $a1 online resource (107 pages) 225 1 $aJSS Research Series in Statistics,$x2364-0065 311 08$a9789811500657 311 08$a9811500657 327 $a1. All-Pairwise Comparisons in Homoscedastic Multi-Sample Models -- 2. Multiple Comparisons in Heteroscedastic Multi-Sample Models -- 3. Multiple Comparison Procedures under Simple Order Restrictions -- 4.: Nonparametric Procedures Based on Rank Statistics -- 5. Comparing the Simulated Power of Multiple Comparison Tests -- 6. Application of Multiple Comparison Tests to Real Data -- 7. Computation of Distribution Functions for Statistics under Simple Ordered Restrictions -- 8. Related Topics -- Index. 330 $aThis book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing closed testing procedures based on maximum absolute values of some two-sample t-test statistics and on F-test statistics in homoscedastic multi-sample models. It shows that (1) the multi-step procedures are more powerful than single-step procedures and the Ryan/Einot?Gabriel/Welsh tests, and (2) the confidence regions induced by the multi-step procedures are equivalent to simultaneous confidence intervals. Next, it describes the multi-step test procedure in heteroscedastic multi-sample models, which is superior to the single-step Games?Howell procedure. In the context of simple ordered restrictions of means, the authors also discuss closed testing procedures based on maximum values of two-sample one-sided t-test statistics and based on Bartholomew's statistics. Furthermore, the book presents distribution-free procedures and describes simulation studies performed under the null hypothesis and some alternative hypotheses. Although single-step multiple comparison procedures are generally used, the closed testing procedures described are more powerful than the single-step procedures. In order to execute the multiple comparison procedures, the upper 100? percentiles of the complicated distributions are required. Classical integral formulas such as Simpson's rule and the Gaussian rule have been used for the calculation of the integral transform that appears in statistical calculations. However, these formulas are not effective for the complicated distribution. As such, the authors introduce the sinc method, which is optimal in terms of accuracy and computational cost. 410 0$aJSS Research Series in Statistics,$x2364-0065 606 $aStatistics 606 $aStatistics 606 $aMathematics$xData processing 606 $aBiotechnology 606 $aStatistical Theory and Methods 606 $aApplied Statistics 606 $aComputational Mathematics and Numerical Analysis 606 $aBiotechnology 615 0$aStatistics. 615 0$aStatistics. 615 0$aMathematics$xData processing. 615 0$aBiotechnology. 615 14$aStatistical Theory and Methods. 615 24$aApplied Statistics. 615 24$aComputational Mathematics and Numerical Analysis. 615 24$aBiotechnology. 676 $a519.538 700 $aShiraishi$b Taka-aki$4aut$4http://id.loc.gov/vocabulary/relators/aut$0782100 702 $aSugiura$b Hiroshi$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aMatsuda$b Shin-ichi$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910350243403321 996 $aPairwise Multiple Comparisons$92530460 997 $aUNINA