Exact Analysis of Discrete DataResearchers in fields ranging from biology and medicine to the social sciences, law, and economics regularly encounter variables that are discrete or categorical in nature. While there is no dearth of books on the analysis and interpretation of such data, these generally focus on large sample methods. When sample sizes are not large or the data are |
Contents
1 | |
OneSided Univariate Analysis | 29 |
TwoSided Univariate Analysis | 55 |
Computing Fundamentals | 87 |
Elements of Conditional Analysis | 117 |
Two 2 2 Tables | 159 |
Assessing Inference | 189 |
Several 2 2 Tables I | 227 |
The 2 K Table | 279 |
Polynomial Algorithms I | 323 |
Polynomial Algorithms II | 349 |
Multinomial Models | 377 |
Matched and Dependent Data | 415 |
Reflections On Exactness | 449 |
485 | |
515 | |
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Common terms and phrases
Algorithm analysis apply approach associated assume asymptotic binary binomial called Chapter checks clinical trial coefficients compute conditional distribution confidence intervals consider construct continuous define denote derived developed discrete data distribution effect efficient equal equation equivalent estimate evidence function exact analysis exact conditional example exponent factor fixed formulation Further given gives Hirji implement independent indicator inference interaction inverse large sample likelihood limits margins mean methods mid-p multiplication nominal Note null observed obtained odds ratio one-sided ordered outcome p-value parameter perform Poisson polynomial practice probability problem random references relevant respectively response risk score space specific statistic Step subjects sufficient Suppose Table tail Theorem treatment unconditional values variable Wald
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References to this book
ICCS 2007: Proceedings of the 15th International Workshops on Conceptual ... Babak Akhgar Limited preview - 2009 |