search for books and compare prices
Tables of Contents for Visualizing Categorical Data
Chapter/Section Title
Page #
Page Count
Preface
ix
How to Use This Book
x
Overview
x
Acknowledgments
xi
Introduction
1
16
Data Visualization and Categorical Data
1
1
What Is Categorical Data?
2
3
Case Form vs. Frequency Form
3
1
Frequency Data vs. Count Data
4
1
Univariate, Bivariate, and Multivariate Data
4
1
Explanatory vs. Response Variables
4
1
Strategies for Categorical Data Analysis
5
3
Hypothesis-Testing Approaches
5
1
Model-Building Approaches
6
2
Graphical Methods for Categorical Data
8
5
Goals and Design Principles for Visual Data Display
8
3
Categorical Data Requires Different Graphical Methods
11
2
Visualization = Graphing + Fitting + Graphing
13
4
Static vs. Dynamic Graphics
15
2
Fitting and Graphing Discrete Distributions
17
42
Introduction
17
5
Discrete Distributions
22
11
The Binomial Distribution
22
4
The Poisson Distribution
26
3
The Negative Binomial Distribution
29
2
The Geometric Distribution
31
1
The Logarithmic Series Distribution
32
1
Power Series Family
32
1
Fitting Discrete Distributions
33
13
The Goodfit Macro
34
4
Plots of Observed and Fitted Frequencies
38
2
The Rootgram Macro
40
2
Maximum Likelihood Estimation
42
1
Fitting Discrete Distributions as Loglinear Models
43
3
Diagnosing Discrete Distributions: Ord Plots
46
3
Poissonness Plot
49
7
Features of the Poissonness Plot
49
1
Plot Construction
49
2
The Poisplot Macro
51
2
Leverage and Influence
53
2
Plots for Other Distributions
55
1
Distplot Macro
55
1
Chapter Summary
56
3
2-Way Contingency Tables
59
46
Introduction
59
3
Tests of Association for 2-Way Tables
62
8
Notation and Terminology
62
1
2 x 2 Tables
63
2
Larger Tables: Overall Analysis
65
2
Tests for Ordinal Variables
67
1
Sample CMH Profiles
68
2
Stratified Analysis
70
4
Assessing Homogeneity of Association
73
1
Fourfold Display for 2 x 2 Tables
74
11
Confidence Rings for Odds Ratio
77
1
The Fourfold Program
78
1
Stratified Analysis for 2 x 2 x k Tables
79
6
Sieve Diagrams
85
5
The Sieve Program
87
1
Larger Tables
88
2
Association Plots
90
1
Observer Agreement
91
6
Measuring Agreement
92
2
Bangdiwala's Observer Agreement Chart
94
2
Observer Bias
96
1
The Agree Program
97
1
Trilinear Plots
97
5
Chapter Summary
102
3
Mosaic Displays for n-Way Tables
105
36
Introduction
105
1
2-Way Tables
106
10
Software for Mosaic Displays
110
6
3-Way Tables
116
13
Fitting Models
117
3
Causal Models
120
6
Partial Association
126
3
Mosaic Matrices for Categorical Data
129
5
Conditional Mosaic Matrices
133
1
Showing the Structure of Log-linear Models
134
5
Mutual Independence
134
2
Joint Independence
136
2
Conditional Independence
138
1
Chapter Summary
139
2
Correspondence Analysis
141
54
Introduction
141
2
Simple Correspondence Analysis
143
11
Notation and Terminology
143
1
Geometric and Statistical Properties
144
1
The Corresp Procedure
145
4
The Corresp Macro
149
4
Quasi-Independence and Structural Zeros
153
1
Properties of Category Scores
154
6
Optimal Category Scores
154
2
Simultaneous Linear Regressions
156
4
Multi-Way Tables
160
5
Marginal Tables and Supplementary Variables
164
1
Multiple Correspondence Analysis
165
12
Bivariate MCA
165
4
The Burt Matrix
169
1
Multivariate MCA
169
8
Extended MCA: Showing Interactions in 2Q Tables
177
11
Biplots for Contingency Tables
188
5
Biplots for 2-Way Tables
188
3
Biplots for 3-Way Tables
191
2
Chapter Summary
193
2
Logistic Regression
195
70
Introduction
195
1
The Logistic Regression Model
196
6
Plotting a Discrete Response: The Logodds Macro
199
1
Plotting a Discrete Response: Easy Smoothing with Proc Gplot
200
2
Models for Quantitative Predictors
202
10
Fitting Logistic Regression Models
202
2
Plotting Predicted Probabilities
204
8
Logit Models for Qualitative Predictors
212
5
Plotting Results from Proc Logistic
215
2
Multiple Logistic Regression Models
217
12
Models with Interaction
223
1
Effect Plots from Coefficients
224
5
Influence and Diagnostic Plots
229
11
Residuals and Leverage
229
1
Influence Diagnostics
230
1
Influence Output from Proc Logistic
231
2
Diagnostic Plots of Influence Measures
233
4
Partial Residual and Added-Variable Plots
237
3
Polytomous Response Models
240
14
Ordinal Response: Proportional Odds Model
241
1
Plotting Results from Proc Logistic
242
3
Nested Dichotomies
245
5
Generalized Logits
250
4
The Bradley-Terry-Luce Model for Paired Comparisons
254
5
Power and Sample Size for Logistic Regression
259
4
Binary Predictor: Comparing Two Proportions
259
2
Quantitative Predictor
261
2
Chapter Summary
263
2
Log-linear and Logit Models
265
70
Introduction
265
1
Log-linear Models for Counts
266
3
Log-linear Models as Discrete ANOVA Models
267
1
Log-linear Models as Discrete GLMs
268
1
Log-linear Models for 3-Way Tables
269
1
Fitting Log-linear Models
269
9
Goodness-of-Fit Tests
270
2
Software
272
1
Using PROC CATMOD
272
1
Using PROC GENMOD
273
3
Using SAS/INSIGHT Software
276
2
Logit Models
278
10
Plotting Results for Logit Models
280
3
Zero Frequencies
283
5
Models for Ordinal Variables
288
11
Log-linear Models for Ordinal Variables
289
4
Adjacent Category Logit Models
293
3
Cumulative Logit Models
296
3
An Extended Example
299
9
A Fresh Look
305
3
Influence and Diagnostic Plots for Log-linear Models
308
9
Residuals and Diagnostics for Log-linear Models
308
1
Half-Normal Probability Plots of Residuals
309
1
Model Diagnostics with Proc Genmod and the Inflglim Macro
310
5
Model Diagnostics with Proc Catmod
315
2
Multivariate Responses
317
15
Examining Relations
326
6
Chapter Summary
332
3
Appendix A SAS Programs and Macros
335
54
A.1 The Addvar Macro: Added Variable Plots for Logistic Regression
337
1
A.2 The Agree Program: Observer Agreement Chart
338
1
A.3 The Biplot Macro: Generalized Biplots
339
2
A.4 The Catplot Macro: Plot Results from Proc Catmod
341
2
A.5 The Corresp Macro: Plotting Proc Corresp Results
343
3
A.6 The Distplot Macro: Plots for Discrete Distributions
346
1
A.7 The Dummy Macro: Create Dummy Variables
346
2
A.8 The Fourfold Program: Fourfold Displays for 2 x 2 x k Tables
348
1
A.9 The Goodfit Macro: Goodness-of-Fit for Discrete Distributions
349
1
A.10 The Halfnorm Macro: Half-Normal Plots for Generalized Linear Models
350
2
A.11 The Inflglim Macro: Influence Plots for Generalized Linear Models
352
2
A.12 The Inflogis Macro: Influence Plots for Logistic Regression Models
354
1
A.13 The Interact Macro: Create Interaction Variables
355
1
A.14 The Lags Macro: Lagged Frequencies for Sequential Analysis
355
3
A.15 The Logodds Macro: Plot Empirical Logits for Binary Data
358
1
A.16 The Mosaics Program: SAS/IML Modules for Mosaic Displays
359
4
A.17 The Mosaic Macro: Mosaic Displays
363
2
A.18 The Mosmat Macro: Mosaic Matrices
365
1
A.19 The Ordplot Macro: Ord Plot for Discrete Distributions
366
1
A.20 The Panels Macro: Arrange Multiple Plots in Panels
367
1
A.21 The Poisplot Macro: Poissonness Plot
368
1
A.22 The Powerlog Macro: Power Analysis for Logistic Regression Table
369
1
A.23 The Powerrxc Macro: Power for 2-Way Frequency Tables
370
1
A.24 The Power2x2 Macro: Power for 2 x 2 Frequency Tables
371
2
A.25 The Robust Macro: Robust Fitting for Linear Models
373
1
A.26 The Rootgram Macro: Hanging Rootograms
373
1
A.27 The Sieve Program: Sieve Diagrams
374
1
A.28 The Sort Macro: Sort a Dataset by the Value of a Statistic
375
2
A.29 The Table Macro: Construct a Grouped Frequency Table, with Recoding
377
1
A.30 The Triplot Macro: Trilinear Plots for n x 3 Tables
378
1
A.31 Utility Macros
379
10
A.31.1 Bars: Create an Annotate Dataset to Draw Error Bars
379
2
A.31.2 Equate: Create Axis Statements for a Gplot with Equated Axes
381
1
A.31.3 Gdispla: Device-Independent Display/Nodisplay Control
382
1
A.31.4 Gensym: Generate Symbol Statements for Multiple Curves
382
1
A.31.5 Gskip: Device Independent Macro for Multiple Plots
383
2
A.31.6 Label: Label Points on a Plot
385
1
A.31.7 Points: Create an Annotate Dataset to Draw Points in a Plot
386
1
A.31.8 Pscale: Construct an Annotate Dataset for a Probability Scale
387
2
Appendix B Datasets
389
20
B.1 arthrit.sas: Arthritis Treatment Data
390
1
B.2 berkeley.sas: Berkeley Admissions Data
391
1
B.3 haireye.sas: Hair-color and Eye-color Data
392
1
B.4 icu.sas: ICU Data
392
2
B.5 lifeboat.sas: Lifeboats on the Titanic
394
3
B.6 marital.sas: Pre-marital Sex, Extra-marital Sex, and Divorce
397
1
B.7 mental.sas: Mental Impairment and Parents' SES
397
1
B.8 msdiag.sas: Diagnosis of Multiple Sclerosis
398
1
B.9 orings.sas: NASA Space Shuttle 0-Ring Failures
399
1
B.10 suicide.sas: Suicide Rates in Germany
399
2
B.11 titanic.sas: Survival on the Titanic
401
1
B.12 vietnam.sas: Student Opinion about the Vietnam War
402
1
B.13 vision.sas: Visual Acuity in Left and Right Eyes
403
1
B.14 vonbort.sas: Deaths by Horse Kicks in the Prussian Army
404
1
B.15 vote.sas: Race and Politics in the 1980 U.S. Presidential Vote
404
1
B.16 wlfdata.sas: Women's Labor-force Participation
405
4
Appendix C Tables
409
4
C.1 Chi2tab Program
410
1
C.2 X2 Values
411
1
C.3 X2/df Values
412
1
References
413
8
Author Index
421
2
Example Index
423
4
Subject Index
427