000			02087nam a2200289Ia 4500
003			OSt
005			20260102093835.0
008			220909b |||||||| |||| 00| 0 eng d
020			_a9780470922255
037			_cTextbook
040			_aCSL _beng _cCSL
041			_aeng
084			_aB284 Q2;1 TB _qCSL
100			_aO'Gorman, Thomas W. _eauthor _9861100
245		0	_aAdaptive Tests of Significance Using Permutations of Residuals with R and SAS
260			_aHoboken : _bWiley , _c2012 .
300			_axvii,345p.
500			_aIncludes References 333-340p.; Index 341-345p.
520			_aAdaptive Tests of Significance Using Permutations of Residuals with R and SAS illustrates the power of adaptive tests and showcases their ability to adjust the testing method to suit a particular set of data. The book utilizes state-of-the-art software to demonstrate the practicality and benefits for data analysis in various fields of study. Beginning with an introduction, the book moves on to explore the underlying concepts of adaptive tests, including, Smoothing methods and normalizing transformations Permutation tests with linear methods Applications of adaptive tests, Multicenter and cross-over trials, Analysis of repeated measures data Adaptive confidence intervals and estimates, Throughout the book, numerous figures illustrate the key differences among traditional tests, nonparametric tests, and adaptive tests. R and SAS software packages are used to perform the discussed techniques, and the accompanying datasets are available on the book's related website. In addition, exercises at the end of most chapters enable readers to analyze the presented datasets by putting new concepts into practice.
650			_aComputer adaptive testing. _9861101
650			_aR computer program language. _9861102
650			_aRegression analysis. _9861103
650			_aSAS computer file. _9861104
650			_aStatistics. _9861105
942			_hB284 Q2;1 TB _cTB _2CC _n0
999			_c8322 _d8322