SPSS Exact Tests

# SPSS Exact Tests - Exact Tests Cyrus R. Mehta and Nitin R....

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Exact Tests Cyrus R. Mehta and Nitin R. Patel

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iii Preface Exact Tests is a statistical package for analyzing continuous or categorical data by ex- act methods. The goal in Exact Tests is to enable you to make reliable inferences when your data are small, sparse, heavily tied, or unbalanced and the validity of the corre- sponding large sample theory is in doubt. This is achieved by computing exact p values for a very wide class of hypothesis tests, including one-, two-, and K- sample tests, tests for unordered and ordered categorical data, and tests for measures of association. The statistical methodology underlying these exact tests is well established in the sta- tistical literature and may be regarded as a natural generalization of Fisher’s exact test for the single contingency table. It is fully explained in this user manual. The real challenge has been to make this methodology operational through software devel- opment. Historically, this has been a difficult task because the computational demands imposed by the exact methods are rather severe. We and our colleagues at the Harvard School of Public Health have worked on these computational problems for over a de- cade and have developed exact and Monte Carlo algorithms to solve them. These algo- rithms have now been implemented in Exact Tests. For small data sets, the algorithms ensure quick computation of exact p values. If a data set is too large for the exact algo- rithms, Monte Carlo algorithms are substituted in their place in order to estimate the exact p values to any desired level of accuracy.

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## This note was uploaded on 06/11/2010 for the course PSYC 588 taught by Professor Hong during the Spring '08 term at University of Illinois, Urbana Champaign.

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SPSS Exact Tests - Exact Tests Cyrus R. Mehta and Nitin R....

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