Introduction to Categorical Data Analysis

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An Introduction to Categorical Data Analysis Second Edition ALAN AGRESTI Department of Statistics University of Florida Gainesville, Florida
Page 1: www.dbeBooks.com - An Ebook Library
Page 6 and 7: An Introduction to Categorical Data
Page 8 and 9: Contents Preface to the Second Edit
Page 10 and 11: CONTENTS vii 3. Generalized Linear
Page 12 and 13: CONTENTS ix 5.2.3 Checking Fit: Gro
Page 14 and 15: CONTENTS xi 7.5 Modeling Ordinal As
Page 16: CONTENTS xiii 10.3 Extensions to Mu
Page 19 and 20: xvi PREFACE TO THE SECOND EDITION f
Page 22 and 23: CHAPTER 1 Introduction From helping
Page 24 and 25: 1.2 PROBABILITY DISTRIBUTIONS FOR C
Page 26 and 27: 1.2 PROBABILITY DISTRIBUTIONS FOR C
Page 28 and 29: 1.3 STATISTICAL INFERENCE FOR A PRO
Page 30 and 31: 1.3 STATISTICAL INFERENCE FOR A PRO
Page 32 and 33: 1.4 MORE ON STATISTICAL INFERENCE F
Page 38 and 39: PROBLEMS 17 a. Specify the distribu
Page 40 and 41: PROBLEMS 19 a. What happens when yo
Page 42 and 43: CHAPTER 2 Contingency Tables Table
Page 44 and 45: 2.1 PROBABILITY STRUCTURE FOR CONTI
Page 46 and 47: 2.2 COMPARING PROPORTIONS IN TWO-BY
Page 48 and 49: 2.2 COMPARING PROPORTIONS IN TWO-BY
Page 50 and 51: 2.3 THE ODDS RATIO 29 In 2 × 2 tab
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2.3 THE ODDS RATIO 31 Because the s
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2.3 THE ODDS RATIO 33 the “no”
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2.4 CHI-SQUARED TESTS OF INDEPENDEN
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2.5 TESTING INDEPENDENCE FOR ORDINA
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2.5 TESTING INDEPENDENCE FOR ORDINA
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2.6 EXACT INFERENCE FOR SMALL SAMPL
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2.6 EXACT INFERENCE FOR SMALL SAMPL
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2.7 ASSOCIATION IN THREE-WAY TABLES
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PROBLEMS 55 PROBLEMS 2.1 An article
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PROBLEMS 57 What is wrong with this
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PROBLEMS 59 same sex and within the
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PROBLEMS 61 Table 2.15. Data for Pr
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PROBLEMS 63 Table 2.17. Data for Pr
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CHAPTER 3 Generalized Linear Models
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3.1 COMPONENTS OF A GENERALIZED LIN
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3.2 GENERALIZED LINEAR MODELS FOR B
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3.3 GENERALIZED LINEAR MODELS FOR C
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3 3 26.5 1.97 1 3 3 24.5 2.20 1 3 3
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3.4 STATISTICAL INFERENCE AND MODEL
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3.4 STATISTICAL INFERENCE AND MODEL
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3.5 FITTING GENERALIZED LINEAR MODE
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PROBLEMS 91 Figure 3.8. Total vote,
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PROBLEMS 93 in millions of lira, th
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PROBLEMS 95 3.15 A recent General S
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PROBLEMS 97 ML estimate ˆβ =−0.
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CHAPTER 4 Logistic Regression Let u
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4.1 INTERPRETING THE LOGISTIC REGRE
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4.2 INFERENCE FOR LOGISTIC REGRESSI
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4.2 INFERENCE FOR LOGISTIC REGRESSI
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4.3 LOGISTIC REGRESSION WITH CATEGO
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4.3 LOGISTIC REGRESSION WITH CATEGO
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4.4 MULTIPLE LOGISTIC REGRESSION 11
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PROBLEMS 121 Table 4.7. Summary of
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PROBLEMS 123 b. Construct a Wald co
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PROBLEMS 125 large increase, so con
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PROBLEMS 127 4.15 Table 4.12 refers
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4.5 PROBLEMS 129 Table 4.15. Table
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PROBLEMS 131 Table 4.17. Table for
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PROBLEMS 133 4.26 Model (4.11) for
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PROBLEMS 135 work in the Northeast;
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CHAPTER 5 Building and Applying Log
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5.1 STRATEGIES IN MODEL SELECTION 1
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5.2 MODEL CHECKING 145 increases. M
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5.2 MODEL CHECKING 147 raw 0 and 1
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5.2 MODEL CHECKING 149 5.2.5 Exampl
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5.2 MODEL CHECKING 151 3. The chang
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5.3 EFFECTS OF SPARSE DATA 153 Figu
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5.3 EFFECTS OF SPARSE DATA 155 Tabl
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5.4 CONDITIONAL LOGISTIC REGRESSION
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5.4 CONDITIONAL LOGISTIC REGRESSION
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5.5 SAMPLE SIZE AND POWER FOR LOGIS
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PROBLEMS 163 PROBLEMS 5.1 For the h
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PROBLEMS 165 c. The concordance ind
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PROBLEMS 167 2001) contains such a
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PROBLEMS 169 table, collapsed over
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PROBLEMS 171 b. Try to fit a main-e
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CHAPTER 6 Multicategory Logit Model
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6.1 LOGIT MODELS FOR NOMINAL RESPON
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6.2 CUMULATIVE LOGIT MODELS FOR ORD
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6.3 PAIRED-CATEGORY ORDINAL LOGITS
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6.3 PAIRED-CATEGORY ORDINAL LOGITS
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6.4 TESTS OF CONDITIONAL INDEPENDEN
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6.4 TESTS OF CONDITIONAL INDEPENDEN
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PROBLEMS 197 6.3 Table 6.14 display
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PROBLEMS 199 Table 6.16. Output on
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PROBLEMS 201 6.13 Fit an adjacent-c
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PROBLEMS 203 a. Show that the Pears
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7.1 LOGLINEAR MODELS FOR TWO-WAY AN
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7.2 INFERENCE FOR LOGLINEAR MODELS
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7.3 THE LOGLINEAR-LOGISTIC CONNECTI
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7.3 THE LOGLINEAR-LOGISTIC CONNECTI
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7.4 INDEPENDENCE GRAPHS AND COLLAPS
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7.5 MODELING ORDINAL ASSOCIATIONS 2
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7.5 MODELING ORDINAL ASSOCIATIONS 2
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PROBLEMS 233 7.2 For the saturated
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PROBLEMS 235 7.5 Refer to Table 2.1
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PROBLEMS 237 c. The estimates shown
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PROBLEMS 239 Table 7.25. Opinions a
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PROBLEMS 241 7.17 For a multiway co
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PROBLEMS 243 with ordered scores {u
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8.1 COMPARING DEPENDENT PROPORTIONS
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8.2 LOGISTIC REGRESSION FOR MATCHED
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8.3 COMPARING MARGINS OF SQUARE CON
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8.3 COMPARING MARGINS OF SQUARE CON
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8.4 SYMMETRY AND QUASI-SYMMETRY MOD
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8.4 SYMMETRY AND QUASI-SYMMETRY MOD
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8.5 ANALYZING RATER AGREEMENT 261 t
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8.5 ANALYZING RATER AGREEMENT 263 t
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8.6 BRADLEY-TERRY MODEL FOR PAIRED
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PROBLEMS 267 Table 8.10. Data from
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PROBLEMS 269 b. Find the McNemar z
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PROBLEMS 271 c. For the symmetry mo
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PROBLEMS 273 8.22 In 1990, a sample
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PROBLEMS 275 8.28 For matched pairs
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9.1 MARGINAL MODELS VERSUS CONDITIO
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9.2 MARGINAL MODELING: THE GEE APPR
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9.3 EXTENDING GEE: MULTINOMIAL RESP
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9.3 EXTENDING GEE: MULTINOMIAL RESP
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9.4 TRANSITIONAL MODELING, GIVEN TH
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PROBLEMS 291 9.2 Refer to Table 7.1
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Table 9.10. Pig Farmer Data for Pro
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PROBLEMS 295 Table 9.12. Computer O
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CHAPTER 10 Random Effects: Generali
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10.1 RANDOM EFFECTS MODELING OF CLU
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10.1 RANDOM EFFECTS MODELING OF CLU
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10.2 EXAMPLES OF RANDOM EFFECTS MOD
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10.3 EXTENSIONS TO MULTINOMIAL RESP
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10.4 MULTILEVEL (HIERARCHICAL) MODE
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10.4 MULTILEVEL (HIERARCHICAL) MODE
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10.5 MODEL FITTING AND INFERENCE FO
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PROBLEMS 319 and yi = number of tho
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PROBLEMS 321 10.10 For the previous
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PROBLEMS 323 Table 10.12. Response
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CHAPTER 11 A Historical Tour of Cat
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11.2 R. A. FISHER’S CONTRIBUTIONS
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11.4 MULTIWAY CONTINGENCY TABLES AN
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11.5 FINAL COMMENTS 331 Research at
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CHAPTER 2: CONTINGENCY TABLES 333 o
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CHAPTERS 4 AND 5: LOGISTIC REGRESSI
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CHAPTER 7: LOGLINEAR MODELS FOR CON
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CHAPTER 8: MODELS FOR MATCHED PAIRS
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CHAPTER 10: RANDOM EFFECTS: GENERAL
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Appendix B: Chi-Squared Distributio
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BIBLIOGRAPHY 345 Hosmer, D. W. and
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INDEX OF EXAMPLES 347 cigarettes, m
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INDEX OF EXAMPLES 349 soccer odds (
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SUBJECT INDEX 351 Classification ta
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SUBJECT INDEX 353 Joint distributio
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SUBJECT INDEX 355 ordinal versus no
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Brief Solutions to Some Odd-Numbere
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CHAPTER 2 359 b. CI for log odds ra
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CHAPTER 4 361 15. a. exp(−2.38 +
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CHAPTER 5 363 ratio = 1.40 has CI (
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CHAPTER 6 365 19. a. logit(π) = α
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CHAPTER 7 367 3. a. G 2 = 0.48, df
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CHAPTER 8 369 11. 95% CI for β is
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CHAPTER 10 371 CHAPTER 10 1. a. Usi
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Introduction to Categorical Data Analysis

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