By Alan Agresti
Praise for the 1st Edition
"This is a wonderful textual content from which to coach specific info research, at quite a few degrees. . . [t]his publication should be very hugely recommended."
—Short e-book Reviews
"Of nice curiosity to strength readers is the range of fields which are represented within the examples: health and wellbeing care, monetary, executive, product advertising, and activities, to call a few."
—Journal of caliber Technology
"Alan Agresti has written one other exceptional account of the research of specific data."
The use of statistical equipment for express info is ever expanding in today's international. An advent to express facts research, moment Edition offers an utilized advent to an important equipment for examining specific info. This new version summarizes equipment that experience lengthy performed a well-known function in facts research, akin to chi-squared exams, and in addition areas particular emphasis on logistic regression and different modeling concepts for univariate and correlated multivariate express responses.
This moment variation features:* new chapters at the equipment for clustered info, with an emphasis on generalized estimating equations (GEE) and random results versions* A unified viewpoint in keeping with generalized linear types* An emphasis on logistic regression modeling* An appendix that demonstrates using SAS(r) for all tools* An wonderful old standpoint at the improvement of the equipment* really good equipment for ordinal information, small samples, multicategory info, and coupled pairs* greater than a hundred analyses of genuine information units and approximately three hundred exercises
Written in an utilized, nontechnical type, the e-book illustrates equipment utilizing a large choice of actual facts, together with clinical medical trials, drug use via kids, basketball capturing, horseshoe crab mating, environmental critiques, correlates of happiness, and masses more.
An advent to specific information research, moment Edition is a useful device for social, behavioral, and biomedical scientists, in addition to researchers in public overall healthiness, advertising and marketing, schooling, organic and agricultural sciences, and business quality controls.
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Extra info for An Introduction to Categorical Data Analysis (Wiley Series in Probability and Statistics)
B. ” Report and interpret the P -value. c. 9 A sample of women suffering from excessive menstrual bleeding have been taking an analgesic designed to diminish the effects. A new analgesic is claimed to provide greater relief. After trying the new analgesic, 40 women reported greater relief with the standard analgesic, and 60 reported greater relief with the new one. a. Test the hypothesis that the probability of greater relief with the standard analgesic is the same as the probability of greater relief with the new analgesic.
That is, when H0 is true, the P -value is equally likely to fall anywhere between 0 and 1. 50. 50. 010, . . 001. 2. 59 In this average sense, P -values for discrete distributions tend to be too large. 5 Inference Based on the Mid P -value∗ With small samples of discrete data, many statisticians prefer to use a different type of P -value. Called the mid P -value, it adds only half the probability of the observed result to the probability of the more extreme results. 011. 006. 2 also shows the mid P -values for the possible y values when n = 10.
The log odds ratio is symmetric about zero, in the sense that reversing rows or reversing columns changes its sign. 7, represent the same strength of association. Doubling a log odds ratio corresponds to squaring an odds ratio. 25. ˆ has a less skewed sampling distribution that is The sample log odds ratio, log θ, bell-shaped. Its approximating normal distribution has a mean of log θ and a standard error of SE = 1 1 1 1 + + + n11 n12 n21 n22 The SE decreases as the cell counts increase. 3 THE ODDS RATIO ˆ it is better Because the sampling distribution is closer to normality for log θˆ than θ, to construct conﬁdence intervals for log θ.
An Introduction to Categorical Data Analysis (Wiley Series in Probability and Statistics) by Alan Agresti