ISBN-10:
0136569277
ISBN-13:
9780136569275
Pub. Date:
12/09/1996
Publisher:
Prentice Hall Professional Technical Reference
SPSS Advanced Statistics 7.5 / Edition 1

SPSS Advanced Statistics 7.5 / Edition 1

by SPSS Inc. Staff, Spss Anc

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Product Details

ISBN-13: 9780136569275
Publisher: Prentice Hall Professional Technical Reference
Publication date: 12/09/1996
Pages: 579
Product dimensions: 7.39(w) x 9.03(h) x 0.92(d)

Table of Contents

1 GLM General Factorial Analysis
1(12)
To Obtain a GLM General Factorial Analysis
2(11)
GLM General Factorial Model
3(2)
GLM Contrasts
5(2)
GLM Profile Plots
7(1)
GLM Post Hoc Multiple Comparisons for Observed Means
8(2)
GLM General Factorial Save
10(1)
GLM General Factorial Options
11(1)
GLM Command Additional Features
12(1)
2 GLM Multivariate Analysis
13(14)
To Obtain a GLM Multivariate Analysis
15(12)
GLM Multivariate Model
16(2)
GLM Multivariate Contrasts
18(1)
GLM Multivariate Profile Plots
19(1)
GLM Multivariate Post Hoc Multiple Comparisons for Observed Means
20(2)
GLM Multivariate Save
22(1)
GLM Multivariate Options
23(1)
GLM Command Additional Features
24(3)
3 GLM Repeated Measures Analysis
27(16)
GLM Repeated Measures Define Factor(s)
29(1)
To Obtain a GLM Repeated Measures Analysis
30(13)
GLM Repeated Measures Model
32(2)
GLM Repeated Measures Contrasts
34(1)
GLM Repeated Measures Profile Plots
35(1)
GLM Repeated Measures Post Hoc Multiple Comparisons for Observed Means
36(2)
GLM Repeated Measures Save
38(1)
GLM Repeated Measures Options
39(1)
GLM Command Additional Features
40(3)
4 Variance Components Analysis
43(6)
To Obtain a Variance Components Analysis
44(5)
Variance Components Model
45(1)
Variance Components Options
46(1)
Sums of Squares (Variance Components)
47(1)
Variance Components Save to a File
48(1)
VARCOMP Command Additional Features
48(1)
5 Model Selection Loglinear Analysis
49(4)
To Obtain a Model Selection Loglinear Analysis
50(3)
Loglinear Analysis Define Range
50(1)
Loglinear Analysis Model
51(1)
Build Terms
51(1)
Loglinear Analysis Options
52(1)
HILOGLINEAR Command Additional Features
52(1)
6 General Loglinear Analysis
53(6)
To Obtain a General Loglinear Analysis
54(3)
General Loglinear Analysis Model
55(1)
General Loglinear Analysis Options
56(1)
To Specify Options
57(2)
General Loglinear Analysis Save
57(1)
GENLOG Command Additional Features
57(2)
7 Logit Loglinear Analysis
59(6)
To Obtain a Logit Loglinear Analysis
60(3)
Logit Loglinear Analysis Model
61(1)
Build Terms
62(1)
Logit Loglinear Analysis Options
62(1)
To Specify Options
63(2)
Logit Loglinear Analysis Save
63(1)
GENLOG Command Additional Features
64(1)
8 Life Tables
65(6)
To Create a Life Table
66(5)
Life Tables Define Event for Status Variable
67(1)
Life Tables Define Range
68(1)
Life Tables Options
68(1)
SURVIVAL Command Additional Features
69(2)
9 Kaplan-Meier Survival Analysis
71(6)
To Obtain a Kaplan-Meier Survival Analysis
72(5)
Kaplan-Meier Define Event for Status Variable
73(1)
Kaplan-Meier Compare Factor Levels
73(1)
Kaplan-Meier Save New Variables
74(1)
Kaplan-Meier Options
74(1)
KM Command Additional Features
75(2)
10 Cox Regression
77(6)
To Obtain a Cox Regression Analysis
78(5)
Cox Regression Define Categorical Variables
79(1)
Cox Regression Plots
80(1)
Cox Regression Save New Variables
81(1)
Cox Regression Options
81(1)
Cox Regression Define Event for Status Variable
82(1)
COXREG Command Additional Features
82(1)
11 Compute Time-Dependent Covariate
83(4)
To Compute a Time-Dependent Covariate
84(3)
Cox W/Time Dep Cov Additional Features
85(2)
12 Using the Matrix Language
87(2)
Using Matrix Commands in a Syntax Window
87(2)
13 Overview of the General Linear Model (GLM) Procedure
89(10)
Examples of Regression and ANOVA
90(9)
Example 1 Regression Model with Two Independent Variables
90(5)
Example 2 Two-Way Analysis of Variance (ANOVA) with Equal Sample Sizes
95(4)
14 General Linear Model Univariate Examples
99(32)
Example 1 Univariate ANOVA: A Randomized Complete Block Design with Two Treatments
100(9)
Estimated Marginal Means and Profile Plots
103(1)
Custom Hypothesis Testing
104(5)
Example 2 Univariate ANOVA: A Randomized Complete Block Design with Empty Cells
109(4)
Example 3 Analysis of Covariance (ANCOVA) and Nesting Using the Interaction Operator
113(7)
Testing Assumptions: Homogeneity of Regression Slopes
114(2)
Analysis-of-Covariance Model
116(2)
A Nested Model Using the Interaction Operator
118(2)
Example 4 Mixed-Effects Nested Design Model
120(7)
Example 5 Univariate Repeated Measures Analysis Using a Split-Plot Design Approach
127(4)
15 General Linear Model Multivariate Examples
131(14)
Example 1 Multivariate ANOVA: Multivariate Two-way Fixed-Effects Model with Interaction
132(4)
Example 2 Profile Analysis: Setting up Custom Linear Hypotheses
136(9)
16 General Linear Model Repeated Measures Examples
145(12)
Example 1 Repeated Measures Analysis of Variance
145(8)
Checking Assumptions
149(2)
Testing Hypotheses
151(2)
Example 2 Doubly Multivariate Repeated Measures Analysis of Variance
153(4)
17 Variance Components Examples
157(22)
Factors, Effects, and Models
157(1)
Types of Factors
157(1)
Types of Effects
158(1)
Types of Models
158(1)
Model for One-Way Classification
158(8)
Estimation Methods
160(5)
Negative Variance Estimates
165(1)
Nested Design Model for Two-Way Classification
166(3)
Univariate Repeated Measures Analysis Using a Mixed Model Approach
169(5)
Background Information
174(5)
Model
174(1)
Distribution Assumptions
175(1)
Estimation Methods
176(3)
18 Model Selection Loglinear Analysis Examples
179(16)
The Loglinear Model
179(4)
The Likelihood-Ratio Chi-square
181(1)
Nested Models
181(1)
Individual Effects
182(1)
Hierarchical Model Selection
183(1)
Strategy for Using Model Selection
184(11)
Example 1 Examining a Saturated Model
185(5)
Example 2 Using Backward Elimination to Select a Suitable Model
190(5)
19 General Loglinear Analysis Examples
195(34)
Parameter Estimation
197(10)
Example 1 Complete Table
198(4)
Example 2 Incomplete Table
202(5)
Background Information
207(5)
Distribution Assumptions
207(2)
Cell Structure Variable
209(1)
Steps in a General Loglinear Analysis
210(2)
Model Diagnosis
212(3)
Goodness-of-Fit Statistics
212(2)
Residuals
214(1)
Additional Examples
215(14)
Example 3 Survival Parametric Model
215(3)
Example 4 Table Standardization
218(4)
Example 5 Poisson Loglinear Regression
222(7)
20 Multinomial Logit Models Examples
229(32)
Example 1 One Response Variable with Two Categories
230(6)
Example 2 Two Response Variables with Two Categories Each
236(6)
Example 3 Polytomous Response Variable
242(6)
Example 4 Model Diagnosis: Coal Miner Data Revisited
248(6)
Example 5 Continuation Ratio Logit Model
254(7)
21 Life Tables Examples
261(10)
When to Use Life Tables
261(1)
Constructing a Life Table
262(3)
Censored Observations
263(1)
Calculating Probabilities
263(1)
Effects of Censoring
264(1)
SPSS Life Tables Output
265(3)
Survival and Hazard Functions
268(3)
Survival Function Plots
268(1)
Comparing Groups
269(2)
22 Kaplan-Meier Survival Analysis Examples
271(14)
Censored Observations
271(1)
When to Use Kaplan-Meier Estimators
271(1)
An Example Using Chemotherapy to Treat Leukemia
272(6)
Computing Cumulative Survival
272(1)
Using Censored Observations
273(1)
SPSS Kaplan-Meier Procedure
274(1)
Comparing Cumulative Survival Functions: Means and Medians
275(1)
Comparing Cumulative Survival Functions: Survival Curves
276(1)
Comparing Cumulative Survival Functions: Tests of Statistical Significance
277(1)
Stratification: The Interaction of Two Variables
278(7)
23 Cox Regression Examples
285(28)
The Cox Regression Model
285(15)
The Hazard Function
286(3)
Generating Cumulative Hazard and Survival Estimates for Individual Cases
289(1)
Plotting Survival Functions
290(1)
Multiple Covariates
291(2)
Testing the Overall Model
293(1)
Finding a Good Model
294(1)
Methods for Selecting Models
294(1)
Stepwise Regression: Forward Selection Example
295(5)
Checking for Proportional Hazards
300(6)
Nonproportional Hazards
301(1)
Cox Regression with Time-Dependent Covariates
302(2)
Segmented Time-Dependent Covariates
304(2)
Diagnostics
306(7)
Using the Partial Residual for Checking Proportional Hazards
307(1)
Linearity of the Log Hazard Function
308(1)
Influential Cases
309(4)
Syntax Reference
313(222)
Introduction
313(6)
COXREG
319(13)
GENLOG
332(11)
GLM: Overview
343(8)
GLM: Univariate
351(21)
GLM: Multivariate
372(5)
GLM: Repeated Measures
377(9)
HILOGLINEAR
386(9)
KM
395(9)
LOGLINEAR
404(14)
MANOVA: Overview
418(4)
MANOVA: Univariate
422(25)
MANOVA: Multivariate
447(13)
MANOVA: Repeated Measures
460(9)
MATRIX--END MATRIX
469(45)
SURVIVAL
514(13)
VARCOMP
527(8)
Appendix A Categorical Variable Coding Schemes
535(6)
Deviation
535(1)
Simple
536(1)
Helmert
537(1)
Difference
537(1)
Polynomial
538(1)
Repeated
539(1)
Special
539(1)
Indicator
540(1)
Appendix B Matrix Macros
541(4)
Limitations of Macros
541(1)
Using the Macros
542(3)
Using the CANCORR Macro
543(1)
Using the RIDGEREG Macro
543(2)
Bibliography 545(4)
Subject Index 549(18)
Syntax Index 567

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