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20 0
Chapter 21
E
Click OK in the Complex Samples Ordinal Regression dialog box.
Pseudo R-Squares
Figure 21-6
Pseudo R-Sq uares
In the linear regression model, the coefficient o f determination, R
2
, summarizes the proportion of
variance in the dependent variable associated with the predictor (independent) variables, with
larger R
2
values indicating that more of the variation is explained by the model, to a maximum
of 1. For regression models with a categorical dependent variable, it is not possible to compute
asingleR
2
statistic that has all of the characteristics of R
2
in the linear regression model, so
these approximations are computed instead. The following methods are used to estimate the
coefficient of determination.
Cox and Snell’s R
2
(Cox and Snell, 1989) is based on the log likelihood for the model
compared to the log likelihood for a baseline model. However, with categorical outcomes, it
has a theoretical maximum value of less than 1, even for a “perfect” model.
Nagelkerke’s R
2
(Nagelkerke, 1991) is an adjusted version of the Cox & Snell R-square that
adjusts the scale of the statistic to cover the full range from 0 to 1.
McFadden’s R
2
(McFadden, 1974) is another version, based on the log-likelihood kernels for
the intercept-only model and the full estimated model.
What constitutes a “good” R
2
value varies between different areas of application. While these
statistics can be suggestive on their own, they are most useful when comparing competing models
for the same data. The model with the largest R
2
statistic is “ best” according to this measure.
Tests of Model Effects
Figure 21-7
Tests of model effects
- IBM SPSS Complex Samples 19 1
- Technical support 3
- Customer Service 3
- Training Seminars 3
- Additional Publications 4
- Contents 5
- Part II: Examples 8
- 17 Complex Sample 9
- 18 Complex Samples Ratios 171 10
- Appendices 12
- A Sample Files 258 12
- B Notices 267 12
- Bibliography 269 12
- Index 271 12
- User’s Guide 13
- Procedures 15
- Plan Files 16
- Further Readings 17
- Creating a New Sample Plan 18
- Chapter 2 20
- Figure 2-2 20
- Sampling Wizard: Sample Size 24
- Define Unequal Sizes 25
- Figure 2-6 26
- Sampling Wizard: Plan Summary 27
- Figure 2-8 28
- Figure 2-9 29
- Sampling Wizard: Finish 30
- Analysis 33
- Creating a New Analysis Plan 34
- Chapter 3 36
- Figure 3-3 36
- Complex Samples Plan 42
- Complex Samples Options 46
- Chapter 7 52
- Figure 7-1 52
- Crosstabs d ialog box 52
- E Click Continue 59
- Select a dependent variable 60
- Optionally, you can: 60
- Figure 9-2 61
- Model dialog box 61
- Non-Nested Terms 70
- Chapter 10 74
- Figure 10-6 74
- CUSTOM subcommand) 77
- ODDSRATIOS subcommand) 77
- CRITERIA subcommand) 77
- SAVE subcommand) 77
- PRINT subcommand) 77
- Figure 11-7 85
- Define Event 91
- Predictors 92
- Subgroups 94
- Figure 12-6 95
- Statistics 96
- Hypothesis Te sts 99
- Chapter 12 102
- Figure 12-11 102
- Part II: 106
- Examples 106
- Using the Wizard 107
- Click Next 108
- Select Yes,addstage2now 111
- Chapter 13 114
- Figure 13-7 114
- 241972 as the value 115
- Click Finish 116
- Plan Summary 117
- Sampling Summary 117
- Sample Results 118
- Select Yes,addstage3now 126
- Figure 13-23 129
- first two stages of that plan 131
- file that you c reated 133
- 4231946 as the value 135
- SELECTION with CPS in 136
- Figure 13-39 145
- Figure 13-45 150
- Stage summary 150
- Related Procedures 153
- Complex Samples Analysis 154
- Preparation Wizard 154
- Preparing 157
- Related P 168
- Complex Samples Frequencies 169
- Click Continue 170
- Frequency Table 172
- Frequency by Subpopulation 172
- Complex Samples Descriptives 174
- Univariate Statistics 177
- Complex Samples Crosstabs 179
- Click Statis tics 181
- Crosstabulation 182
- Risk Estimate 183
- Complex Samples Ratios 185
- 1.3 as the test value 187
- Pivoted Ratios Table 188
- Running the Analysis 190
- Click Model 192
- Model Summary 195
- Tests of Model Effects 195
- Parameter Estimates 196
- Estimated Marginal Means 197
- Pseudo R-Squares 204
- Classification 205
- Odds Ratios 207
- Generalized Cumulative Model 218
- Figure 21-14 219
- Click Options 220
- Warnings 221
- Comparing Models 222
- Preparing the Data 224
- TE.DMY(30,6,2006) 225
- Select Days as the unit 229
- Click Define Event 232
- Click the Predictors tab 233
- Click the Statistics tab 234
- Sample Design Information 235
- Test of Proportional Hazards 236
- Click New 237
- Select t_age as a covariate 238
- Click OK 242
- Type 6 asthenumberofgroups 244
- 1 as the numeric expression 257
- Click the Plots tab 266
- Click the Options tab 267
- Pattern Values 270
- Log-Minus-Log Plot 271
- Sample Files 272
- Appendix 281
- Trademarks 282
- Bibliography 283
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