Statistical models for causal analysis:
Gespeichert in:
| Hauptverfasser: | , |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
New York [u.a.]
Wiley
1993
|
| Schriftenreihe: | A Wiley-Interscience publication
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | XIV, 258 S. graph. Darst. |
| ISBN: | 0471558028 |
Internformat
MARC
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| 100 | 1 | |a Retherford, Robert D. |e Verfasser |4 aut | |
| 245 | 1 | 0 | |a Statistical models for causal analysis |c Robert D. Retherford ; Minja Kim Choe |
| 264 | 1 | |a New York [u.a.] |b Wiley |c 1993 | |
| 300 | |a XIV, 258 S. |b graph. Darst. | ||
| 336 | |b txt |2 rdacontent | ||
| 337 | |b n |2 rdamedia | ||
| 338 | |b nc |2 rdacarrier | ||
| 490 | 0 | |a A Wiley-Interscience publication | |
| 650 | 4 | |a Analyse multivariée | |
| 650 | 7 | |a Analyse multivariée |2 ram | |
| 650 | 7 | |a Causale modellen |2 gtt | |
| 650 | 7 | |a Regressieanalyse |2 gtt | |
| 650 | 4 | |a Multivariate analysis | |
| 650 | 0 | 7 | |a Kausalanalyse |0 (DE-588)4163511-5 |2 gnd |9 rswk-swf |
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| 689 | 0 | |5 DE-604 | |
| 689 | 1 | 0 | |a Multivariate Analyse |0 (DE-588)4040708-1 |D s |
| 689 | 1 | |5 DE-604 | |
| 700 | 1 | |a Choe, Minja K. |e Verfasser |4 aut | |
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| 943 | 1 | |a oai:aleph.bib-bvb.de:BVB01-006695195 | |
Datensatz im Suchindex
| _version_ | 1817681122820096000 |
|---|---|
| adam_text |
CONTENTS
1 Bivariate Linear Regression 1
1.1. Terminology, 1
1.2. Fitting a Least Squares Line, 2
1.3. The Least Squares Line as a Causal Model, 5
1.4. The Bivariate Linear Regression Model
as a Statistical Model, 7
1.4.1. Simplifying Assumptions, 8
1.5. Statistical Inference: Generalizing from Sample
to Underlying Population, 10
1.5.1. Hypothesis Testing, 12
1.5.2. Confidence Intervals, 15
1.5.3. t Values and Z Values, 16
1.5.4. p Value, 17
1.5.5. Importance of a Good Spread of Values
of the Predictor Variable, 18
1.5.6. Beware of Outliers!, 20
1.5.7. Beware of Selection on the Response
Variable!, 21
1.5.8. Presentation of Results, 22
1.6. Goodness of Fit, 23
1.6.1. Standard Error of the Estimate, s, 23
1.6.2. Coefficient of Determination, r2, and
Correlation Coefficient, r, 24
1.7. Further Reading, 28
vii
2 Multiple Regression 29
2.1. The Problem of Bias in Bivariate Linear Regression, 30
2.2. Multiple Regression with Two Predictor
Variables, 31
2.3. Multiple Regression with Three or More Predictor
Variables, 34
2.4. Dummy Variables to Represent Categorical Variables, 34
2.4.1. Categorical Variables with Two Categories, 34
2.4.2. Categorical Variables with More Than Two
Categories, 36
2.5. Multicollinearity, 38
2.6. Interaction, 40
2.6.1. Model Specification, 40
2.6.2. More Complicated Interactions, 43
2.6.3. Correlation without Interaction, 45
2.6.4. Interaction without Correlation, 45
2.7. Nonlinearities, 46
2.7.1. Quadratic Specification, 46
2.7.2. Dummy Variable Specification, 49
2.8. Goodness of Fit, 51
2.8.1. Standard Error of the Estimate, s, 51
2.8.2. Coefficient of Determination, R2, and Multiple
Correlation Coefficient, R, 52
2.8.3. Corrected R2 and Corrected R, 53
2.8.4. Partial Correlation Coefficient, 54
2.9. Statistical Inference, 55
2.9.1. Hypothesis Testing, Confidence Intervals,
and p Values for a Single Regression
Coefficient, 55
2.9.2. Testing the Difference Between Two Regression
Coefficients, /3, and /3y, 56
2.9.3. Testing Effects When There Is Interaction, 57
2.9.4. Testing Effects When There Is a Nonlinearity, 58
2.9.5. The ANOVA Table, 59
2.9.6. The Omnibus F Test of the Hypothesis /3, = /32 =
¦ • • = pk = 0, 60
2.9.7. Test of the Hypothesis That Some of the /3y Are
Zero, 61
2.10. Stepwise Regression, 62
2.11. Illustrative Examples, 63
2.11.1. Example 1, 63
2.11.2. Example 2, 66
2.12. Further Reading, 68
3 Multiple Classification Analysis 69
3.1. The Basic MCA Table, 70
3.1.1. Unadjusted Values, 70
3.1.2. Adjusted Values, 73
3.1.3. Unadjusted and Adjusted, R, 75
3.1.4. A Numerical Example, 76
3.2. The MCA Table in Deviation Form, 78
3.2.1. First Approach to Table Set up, 78
3.2.2. Second Approach to Table Set up, 78
3.2.3. A Numerical Example, 81
3.3. MCA with Interactions, 82
3.3.1. Table Set up, 82
3.3.2. A Numerical Example, 84
3.4. MCA with Additional Quantitative Control Variables, 85
3.4.1. Table Set up, 86
3.4.2. A Numerical Example, 87
3.5. Expressing Results from Ordinary Multiple
Regression in an MCA Format (all Variables
Quantitative), 88
3.5.1. Table Set up, 88
3.5.2. A Numerical Example, 89
3.5.3. Why Present Ordinary Regression Results
in an MCA Format?, 89
3.6. Presenting MCA Results Graphically, 90
3.7. Further Reading, 92
4 Path Analysis 93
4.1. Path Diagrams and Path Coefficients, 93
4.2. Path Models with More Than One Exogenous
Variable, 100
4.3. Path Models with Control Variables, 105
4.4. Saturated and Unsaturated Path Models, 107
4.5. Path Analysis with Standardized Variables, 109
4.5.1. Standardized Variables and Standardized Path
Coefficients, 109
4.5.2. Path Models in Standardized Form, 110
4.5.3. Standardized Versus Unstandardized
Coefficients, 113
4.6. Path Models with Interactions and Nonlinearities, 114
4.7. Further Reading, 118
5 Logit Regression 119
5.1. The Linear Probability Model, 119
5.2. The Logit Regression Model, 121
5.2.1. The Logistic Function, 122
5.2.2. The Multivariate Logistic Function, 125
5.2.3. The Odds and the Logit of P, 126
5.2.4. Logit Regression Coefficients as Measures
of Effect on Logit P, 128
5.2.5. Odds Ratios as Measures of Effect
on the Odds, 129
5.2.6. The Effect on the Odds When the Predictor
Variable Is Categorical with More Than Two
Categories, 132
5.2.7. The Effect of the Predictor Variables
on the Risk P Itself, 134
5.2.8. Interactions, 135
5.2.9. Nonlinearities, 136
5.3. Statistical Inference, 137
5.3.1. Tests of Coefficients, 137
5.3.2. Testing the Difference Between Two Models, 138
5.4. Goodness of Fit, 140
5.5. MCA Adapted to Logit Regression, 142
5.5.1. An Illustrative Example, 142
5.5.2. Table Set up and Numerical Results, 144
5.6. Fitting the Logit Regression Model, 147
5.6.1. The Maximum Likelihood Method, 147
5.6.2. Derivation of the Likelihood Function, 147
5.7. Some Limitations of the Logit Regression Model, 150
5.8. Further Reading, 150
6 Multinomial Logit Regression 151
6.1. From Logit to Multinomial Logit, 151
6.1.1. The Basic Form of the Multinomial
Logit Model, 151
6.1.2. Interpretation of Coefficients, 153
6.1.3. Presentation of Results in a Multiple
Classification Analysis (MCA) Format, 153
6.1.4. Statistical Inference, 157
6.1.5. Goodness of Fit, 157
6.1.6. Changing the Reference Category
of the Response Variable, 157
6.2. Multinomial Logit Models with Interactions and
Nonlinearities, 159
6.3. A More General Formulation of the Multinomial Logit
Model, 160
6.4. Reconceptualizing Contraceptive Method Choice
as a Two Step Process, 163
6.5. Further Reading, 165
7 Survival Models, Part 1: Life Tables 167
7.1. Actuarial Life Table, 168
7.1.1. Statistical Inference, 173
7.2. Product Limit Life Table, 175
7.2.1. Testing the Difference Between Two
Survival Curves, 177
7.3. The Life Table in Continuous Form, 178
7.4. Further Reading, 180
8 Survival Models, Part 2: Proportional Hazard Models 181
8.1. Basic Form of the Proportional Hazard Model, 182
8.1.1. A Simple Example, 183
8.1.2. Addition of a Second Predictor Variable, 184
8.1.3. Redefinition of the Baseline Hazard, 185
8.1.4. Relative Risks as Measures of Effect
on the Hazard, 187
8.1.5. Hazard Regression Coefficients as Measures of Effect
on the Log Hazard, 188
8.1.6. The Effect on the Hazard When the Predictor
Variable Is Categorical with More Than Two
Categories, 190
8.1.7. Interactions, 191
8.1.8. Nonlinearities, 192
8.1.9. Changing the Reference Category
of a Categorical Predictor Variable, 194
8.2. Calculation of Life Tables from the Proportional
Hazard Model, 194
8.2.1. The Hazard Model in Survivorship Form, 194
8.2.2. The Problem of Unobserved Heterogeneity, 195
8.2.3. Test for Proportionality, 196
8.3. Statistical Inference and Goodness of Fit, 198
8.4. A Numerical Example, 198
8.5. Multiple Classification Analysis (MCA) Adapted
to Proportional Hazard Regression, 205
8.6. Further Reading, 205
9 Survival Models, Part 3: Hazard Models
with Time Dependence 207
9.1. Time Dependent Predictor Variables, 207
9.1.1. Coefficients and Effects, 208
9.1.2. Choosing a Baseline Hazard Function, 209
9.1.3. MCA Adapted to Hazard Regression
with Time Dependent Predictor Variables, 210
9.2. Time Dependent Coefficients, 214
9.2.1. Coefficients and Effects, 214
9.2.2. Survival Functions, 216
9.2.3. MCA Adapted to Hazard Regression
with Time Dependent Coefficients, 218
9.3. Further Reading, 220
Appendix A Sample Computer Programs 221
A.I. Description of the FIJIDATA File, 221
A.2. SAS Mainframe Programs, 223
Program 1. SAS Program for Multiple
Regression (Program Used for
Table 2.2), 223
Program 2. SAS Program for Partial
Correlation Coefficient (Program
Used for Table 3.4,
Adjusted R Column), 224
Program 3. SAS Program for Logit
Regression (Program Used
for Table 5.1), 225
Program 4. SAS Program for Multinomial Logit
Regression (Program Used
for Table 6.4), 226
A.3. Preparing Data for Survival Analysis, 227
Program 5. SAS Program to Create Input
Data File for BMDP and
LIMDEP Programs for Life Table
and Hazard Model Analysis
of Progression from Fifth Birth
to Sixth Birth, 228
A.4. BMDP Mainframe Programs, 230
Program 6. BMDP1L Program for
Actuarial Life Table: Progression
from Fifth Birth to Sixth Birth
for Fijians and Indians (Program Used
for Table 7.1 and the Actuarial Life
Tables in Table 7.2), 230
Program 7. BMDP1L Program for
Product Limit Life Table: Progression
from Fifth Birth to Sixth Birth
for Fijians and Indians (Programs Used
for Product Limit Life
Tables in Table 7.2), 232
Program 8. BMDP2L Program for
Proportional Hazard Model:
Progression from
Fifth to Sixth Birth
for Indians (Program Used
for Table 8.1), 233
Program 9. BMDP2L Program
for Hazard Model with Time
Dependent Covariate
(Program Used
for Table 9.2), 235
Program 10. BMDP2L Program
for Hazard Model with Time
Dependent Covariate
and Time Dependent
Effect (Program Used
for Table 9.3), 237
A.5. LIMDEP Programs for IBM Compatible
Personal Computers, 238
Program 11. LIMDEP Program
for Multiple Regression (Program
used for Table 2.2), 238
Program 12. LIMDEP Program
for Partial Correlation Coefficient
(Program Used for Table 3.4,
Adjusted R column), 239
Program 13. LIMDEP Program
for Logit Regression
(Program Used
for Table 5.1), 240
Program 14. LIMDEP Program
for Multinomial Logit Regression
(Program Used
for Table 6.4), 241
Program 15. LIMDEP Program
for Life Table (Actuarial and
Product Limit): Progression
from Fifth Birth
to Sixth Birth, Indians (Program
Used for Table 7.2), 242
Problem 16. LIMDEP Program
for Proportional Hazard Model:
Progression from Fifth
Birth to Sixth Birth,
Indians (Programs Used
for Table 8.1), 243
Problem 17. LIMDEP Program
for Hazard Model with Time
Dependent Covariate: Progression
from Fifth Birth to Sixth
Birth, Indians (Program
Used for Table 9.2), 243
Problem 18. LIMDEP Program for
Hazard Model with Time Dependent
Covariate and Time Dependent
Effect: Progression from Fifth Birth
to Sixth Birth, Indians (Program
Used for Table 9.3), 244
Appendix B Statistical Reference Tables 245
References 251
Index 254 |
| any_adam_object | 1 |
| author | Retherford, Robert D. Choe, Minja K. |
| author_facet | Retherford, Robert D. Choe, Minja K. |
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| ctrlnum | (OCoLC)28722620 (DE-599)BVBBV010088368 |
| dewey-full | 519.5/35 |
| dewey-hundreds | 500 - Natural sciences and mathematics |
| dewey-ones | 519 - Probabilities and applied mathematics |
| dewey-raw | 519.5/35 |
| dewey-search | 519.5/35 |
| dewey-sort | 3519.5 235 |
| dewey-tens | 510 - Mathematics |
| discipline | Mathematik Wirtschaftswissenschaften |
| format | Book |
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| id | DE-604.BV010088368 |
| illustrated | Illustrated |
| indexdate | 2024-12-06T09:03:21Z |
| institution | BVB |
| isbn | 0471558028 |
| language | English |
| oai_aleph_id | oai:aleph.bib-bvb.de:BVB01-006695195 |
| oclc_num | 28722620 |
| open_access_boolean | |
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| owner_facet | DE-703 DE-739 DE-20 DE-29T DE-634 DE-83 DE-11 DE-188 DE-578 |
| physical | XIV, 258 S. graph. Darst. |
| publishDate | 1993 |
| publishDateSearch | 1993 |
| publishDateSort | 1993 |
| publisher | Wiley |
| record_format | marc |
| series2 | A Wiley-Interscience publication |
| spelling | Retherford, Robert D. Verfasser aut Statistical models for causal analysis Robert D. Retherford ; Minja Kim Choe New York [u.a.] Wiley 1993 XIV, 258 S. graph. Darst. txt rdacontent n rdamedia nc rdacarrier A Wiley-Interscience publication Analyse multivariée Analyse multivariée ram Causale modellen gtt Regressieanalyse gtt Multivariate analysis Kausalanalyse (DE-588)4163511-5 gnd rswk-swf Multivariate Analyse (DE-588)4040708-1 gnd rswk-swf Statistisches Modell (DE-588)4121722-6 gnd rswk-swf Kausalanalyse (DE-588)4163511-5 s Statistisches Modell (DE-588)4121722-6 s DE-604 Multivariate Analyse (DE-588)4040708-1 s Choe, Minja K. Verfasser aut HBZ Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006695195&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis |
| spellingShingle | Retherford, Robert D. Choe, Minja K. Statistical models for causal analysis Analyse multivariée Analyse multivariée ram Causale modellen gtt Regressieanalyse gtt Multivariate analysis Kausalanalyse (DE-588)4163511-5 gnd Multivariate Analyse (DE-588)4040708-1 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| subject_GND | (DE-588)4163511-5 (DE-588)4040708-1 (DE-588)4121722-6 |
| title | Statistical models for causal analysis |
| title_auth | Statistical models for causal analysis |
| title_exact_search | Statistical models for causal analysis |
| title_full | Statistical models for causal analysis Robert D. Retherford ; Minja Kim Choe |
| title_fullStr | Statistical models for causal analysis Robert D. Retherford ; Minja Kim Choe |
| title_full_unstemmed | Statistical models for causal analysis Robert D. Retherford ; Minja Kim Choe |
| title_short | Statistical models for causal analysis |
| title_sort | statistical models for causal analysis |
| topic | Analyse multivariée Analyse multivariée ram Causale modellen gtt Regressieanalyse gtt Multivariate analysis Kausalanalyse (DE-588)4163511-5 gnd Multivariate Analyse (DE-588)4040708-1 gnd Statistisches Modell (DE-588)4121722-6 gnd |
| topic_facet | Analyse multivariée Causale modellen Regressieanalyse Multivariate analysis Kausalanalyse Multivariate Analyse Statistisches Modell |
| url | http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=006695195&sequence=000002&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA |
| work_keys_str_mv | AT retherfordrobertd statisticalmodelsforcausalanalysis AT choeminjak statisticalmodelsforcausalanalysis |