New PDF release: An Introduction to Categorical Data Analysis, Second Edition

By Alan Agresti

ISBN-10: 0470114754

ISBN-13: 9780470114759

ISBN-10: 0471226181

ISBN-13: 9780471226185

The 1st variation of this article has offered over 19,600 copies. besides the fact that, using statistical equipment for express information has elevated dramatically in recent times, really for functions within the biomedical and social sciences. A moment variation of the introductory model of the publication will swimsuit it properly. Wiley additionally released a second version of Categorical facts Analysis, that is a sophisticated, extra technical textual content, in 2003.

Chapter 1 creation (pages 1–20):
Chapter 2 Contingency Tables (pages 21–64):
Chapter three Generalized Linear versions (pages 65–98):
Chapter four Logistic Regression (pages 99–136):
Chapter five construction and utilising Logistic Regression types (pages 137–172):
Chapter 6 Multicategory Logit versions (pages 173–203):
Chapter 7 Loglinear versions for Contingency Tables (pages 204–243):
Chapter eight versions for Matched Pairs (pages 244–275):
Chapter nine Modeling Correlated, Clustered Responses (pages 276–296):
Chapter 10 Random results: Generalized Linear combined types (pages 297–324):
Chapter eleven A historic travel of express information research (pages 325–331):

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Additional info for An Introduction to Categorical Data Analysis, Second Edition

Example text

Analyzing associations is at the heart of multivariate statistical analysis. This chapter deals with associations between categorical variables. We introduce parameters that describe the association and we present inferential methods for those parameters. 1 PROBABILITY STRUCTURE FOR CONTINGENCY TABLES For a single categorical variable, we can summarize the data by counting the number of observations in each category. The sample proportions in the categories estimate the category probabilities. An Introduction to Categorical Data Analysis, Second Edition.

D. 133). 13 Refer to the previous exercise, with y = 0 in n = 25 trials. a. 50. b. 0. ) c. 7. Report the P -value. d. 074). 05. 5 found binomial P -values for a clinical trial with y = 9 successes in 10 trials. Suppose instead y = 8. 2: a. 50. b. 50. c. 0 for the mid P -value? 15 If Y is a variate and c is a positive constant, then the standard deviation of the distribution of cY equals cσ (Y ). Suppose Y is a binomial variate, and let p = Y /n. a. √ Based on the binomial standard deviation for Y , show that σ (p) = [π(1 − π)/n].

The test statistics used to make such comparisons have large-sample chi-squared distributions. 6) It was proposed in 1900 by Karl Pearson, the British statistician known also for the Pearson product–moment correlation estimate, among many contributions. This statistic takes its minimum value of zero when all nij = μij . For a fixed sample size, greater differences {nij − μij } produce larger X2 values and stronger evidence against H0 . Since larger X 2 values are more contradictory to H0 , the P -value is the null probability that X 2 is at least as large as the observed value.

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An Introduction to Categorical Data Analysis, Second Edition by Alan Agresti

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