By Alan Agresti
Praise for the 1st Edition
"This is an excellent textual content from which to coach specific facts research, at various degrees. . . [t]his ebook might be very hugely recommended."
—Short e-book Reviews
"Of nice curiosity to capability 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 incredible account of the research of express data."
—The Statistician
The use of statistical equipment for express info is ever expanding in modern global. An advent to specific facts research, moment Edition offers an utilized advent to an important tools for reading specific info. This re-creation summarizes equipment that experience lengthy performed a well-liked function in information research, resembling chi-squared assessments, and likewise areas distinct emphasis on logistic regression and different modeling suggestions for univariate and correlated multivariate specific responses.
This moment version features:
- Two new chapters at the tools for clustered facts, with an emphasis on generalized estimating equations (GEE) and random results models
- A unified point of view in accordance with generalized linear models
- An emphasis on logistic regression modeling
- An appendix that demonstrates using SAS(r) for all methods
- An enjoyable ancient standpoint at the improvement of the methods
- Specialized tools for ordinal information, small samples, multicategory facts, and paired pairs
- More than a hundred analyses of actual info units and approximately three hundred exercises
Written in an utilized, nontechnical kind, the publication illustrates tools utilizing a large choice of genuine information, together with scientific scientific trials, drug use through little ones, basketball capturing, horseshoe crab mating, environmental critiques, correlates of happiness, and lots more and plenty more.
An creation to specific info research, moment Edition is a useful software for social, behavioral, and biomedical scientists, in addition to researchers in public healthiness, advertising, schooling, organic and agricultural sciences, and business caliber control.
Quick preview of An Introduction to Categorical Data Analysis PDF
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Extra resources for An Introduction to Categorical Data Analysis
1. three Sensitivity and Specificity in Diagnostic checks, 23 2. 1. four Independence, 24 2. 1. five Binomial and Multinomial Sampling, 25 2. 2 evaluating Proportions in Two-by-Two Tables, 25 2. 2. 1 distinction of Proportions, 26 2. 2. 2 instance: Aspirin and center assaults, 26 2. 2. three Relative danger, 27 2. three the chances Ratio, 28 2. three. 1 homes of the chances Ratio, 29 2. three. 2 instance: Odds Ratio for Aspirin Use and center assaults, 30 2. three. three Inference for Odds Ratios and Log Odds Ratios, 30 2. three. four courting among Odds Ratio and Relative probability, 32 2. three. five the percentages Ratio Applies in Case–Control experiences, 32 2. three. 6 different types of Observational reports, 34 2. four Chi-Squared assessments of Independence, 34 2. four. 1 Pearson Statistic and the Chi-Squared Distribution, 35 2. four. 2 Likelihood-Ratio Statistic, 36 2. four. three checks of Independence, 36 2. four. four instance: Gender hole in Political Affiliation, 37 2. four. five Residuals for Cells in a Contingency desk, 38 2. four. 6 Partitioning Chi-Squared, 39 2. four. 7 reviews approximately Chi-Squared assessments, forty 2. five trying out Independence for Ordinal facts, forty-one 2. five. 1 Linear pattern replacement to Independence, forty-one 2. five. 2 instance: Alcohol Use and toddler Malformation, forty two 2. five. three additional energy with Ordinal checks, forty three 2. five. four collection of ratings, forty three 2. five. five development checks for I × 2 and a pair of × J Tables, forty four 2. five. 6 Nominal–Ordinal Tables, forty five 2. 6 certain Inference for Small Samples, forty five 2. 6. 1 Fisher’s distinctive attempt for two × 2 Tables, forty five 2. 6. 2 instance: Fisher’s Tea Taster, forty six 2. 6. three P -values and Conservatism for genuine P (Type I Error), forty seven 2. 6. four Small-Sample Confidence period for Odds Ratio, forty eight 2. 7 organization in Three-Way Tables, forty nine 2. 7. 1 Partial Tables, forty nine 2. 7. 2 Conditional as opposed to Marginal institutions: loss of life Penalty instance, forty nine 2. 7. three Simpson’s Paradox, fifty one 2. 7. four Conditional and Marginal Odds Ratios, fifty two 2. 7. five Conditional Independence as opposed to Marginal Independence, fifty three 2. 7. 6 Homogeneous organization, fifty four difficulties, fifty five vii CONTENTS three. Generalized Linear types sixty five three. 1 elements of a Generalized Linear version, sixty six three. 1. 1 Random part, sixty six three. 1. 2 Systematic part, sixty six three. 1. three hyperlink functionality, sixty six three. 1. four common GLM, sixty seven three. 2 Generalized Linear types for Binary facts, sixty eight three. 2. 1 Linear likelihood version, sixty eight three. 2. 2 instance: noisily snoring and center sickness, sixty nine three. 2. three Logistic Regression version, 70 three. 2. four Probit Regression version, seventy two three. 2. five Binary Regression and Cumulative Distribution features, seventy two three. three Generalized Linear types for count number info, seventy four three. three. 1 Poisson Regression, seventy five three. three. 2 instance: woman Horseshoe Crabs and their Satellites, seventy five three. three. three Overdispersion: better Variability than anticipated, eighty three. three. four adverse Binomial Regression, eighty one three. three. five count number Regression for price information, eighty two three. three. 6 instance: British teach injuries through the years, eighty three three. four Statistical Inference and version Checking, eighty four three. four. 1 Inference approximately version Parameters, eighty four three. four. 2 instance: noisily snoring and center disorder Revisited, eighty five three. four. three The Deviance, eighty five three. four. four version comparability utilizing the Deviance, 86 three. four. five Residuals evaluating Observations to the version healthy, 87 three. five becoming Generalized Linear types, 88 three. five. 1 The Newton–Raphson set of rules suits GLMs, 88 three.