Pairwise Multiple Comparisons

Name: Pairwise Multiple Comparisons
Brand: Springer Nature Singapore
SKU: 9789811500657
Price: 254.58 PLN
Availability: InStock

Autor: Hiroshi Sugiura, Shin-Ichi Matsuda

Język:

Oprawa: Miękka

Wydawca: Springer Nature Singapore

Dostępność: Dostępna u dostawcy

Wysyłamy za 5-8 dni

254.58 zł

This book focuses on all-pairwise multiple comparisons of means in multi-sample models, introducing...

Informacje o książce

Autor

Hiroshi Sugiura, Shin-Ichi Matsuda

Język

Angielski

Oprawa

Książka - Miękka

Data wydania

2019

strony

102

EAN

9789811500657

ISBN

9811500657

Enbook ID

24319536

Wydawca

Springer Nature Singapore

Waga

186

Wymiary

155 x 235 x 7

Pełny opis

This 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.

Możesz być zainteresowany

Klienci, którzy kupili tę książkę, kupili również

Najczęściej wyszukiwane

Categories

Authors

Publishers

Produkty

Produkty

Najczęściej wyszukiwane

Categories

Authors

Publishers

Produkty

Produkty

Pairwise Multiple Comparisons

Informacje o książce

Pełny opis

Możesz być zainteresowany

Klienci, którzy kupili tę książkę, kupili również