By Alan Agresti
Praise for the 1st Edition
"This is a wonderful textual content from which to coach express info research, at a number of degrees. . . [t]his e-book might be very hugely recommended."
—Short publication Reviews
"Of nice curiosity to strength readers is the diversity 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 wonderful account of the research of specific data."
The use of statistical equipment for specific facts is ever expanding in today's international. An creation to express info research, moment Edition presents an utilized advent to an important equipment for examining specific info. This new version summarizes equipment that experience lengthy performed a renowned function in information research, equivalent to chi-squared exams, and in addition locations detailed emphasis on logistic regression and different modeling thoughts for univariate and correlated multivariate specific responses.
This moment variation features:* new chapters at the equipment for clustered facts, with an emphasis on generalized estimating equations (GEE) and random results versions* A unified point of view according to generalized linear types* An emphasis on logistic regression modeling* An appendix that demonstrates using SAS(r) for all tools* An enjoyable ancient standpoint at the improvement of the tools* really expert tools for ordinal info, small samples, multicategory info, and coupled pairs* greater than a hundred analyses of genuine info units and approximately three hundred exercises
Written in an utilized, nontechnical variety, the publication illustrates equipment utilizing a large choice of genuine information, together with scientific medical trials, drug use via young children, basketball capturing, horseshoe crab mating, environmental reviews, correlates of happiness, and masses more.
An advent to specific facts research, moment Edition is a useful device for social, behavioral, and biomedical scientists, in addition to researchers in public healthiness, advertising, schooling, organic and agricultural sciences, and commercial quality controls.
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Additional info for An Introduction to Categorical Data Analysis (Wiley Series in Probability and Statistics)
2 on aspirin use and myocardial infarction. 0174. 74 “yes” outcomes for every 100 “no” outcomes. 95 “yes” outcomes per every 100 “no” outcomes. 832. This also equals the cross-product ratio (189 × 10, 933)/(10,845 × 104). 83 times the estimated odds for male physicians taking aspirin. The estimated odds were 83% higher for the placebo group. 3 Inference for Odds Ratios and Log Odds Ratios Unless the sample size is extremely large, the sampling distribution of the odds ratio is highly skewed. When θ = 1, for example, θˆ cannot be much smaller than θ (since θˆ ≥ 0), but it could be much larger with nonnegligible probability.
Of women who get mammograms at any given time, it has been estimated that 1% truly have breast cancer. 88. 07. 2). 1. 88. How can P (X = 1|Y = 1) be so low, given the relatively good sensitivity and speciﬁcity? 1 is a tree diagram that shows results for a typical sample of 100 women. The ﬁrst set of branches shows whether a woman has breast cancer. Here, one of the 100 women have it, 1% of the sample. The second set of branches shows the mammogram result, given the disease status. 86 probability of detecting it.
3 reported. 83 times p2 . This relationship between the odds ratio and the relative risk is useful. For some data sets direct estimation of the relative risk is not possible, yet one can estimate the odds ratio and use it to approximate the relative risk, as the next example illustrates. 4 refers to a study that investigated the relationship between smoking and myocardial infarction. The ﬁrst column refers to 262 young and middle-aged women (age < 69) admitted to 30 coronary care units in northern Italy with acute MI during a 5-year period.