A gentle introduction to Stata:
Gespeichert in:
| 1. Verfasser: | |
|---|---|
| Format: | Buch |
| Sprache: | English |
| Veröffentlicht: |
College Station, Tex.
Stata Press
2006
|
| Schlagworte: | |
| Online-Zugang: | Inhaltsverzeichnis |
| Beschreibung: | 289 S. graph. Darst. |
| ISBN: | 1597180092 |
Internformat
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Datensatz im Suchindex
| _version_ | 1804135256342659072 |
|---|---|
| adam_text | Contents
Preface xix
Support materials for the book xxi
1 Getting started 1
1.1 Introduction 1
1.2 The Stata screen 3
1.3 Using an existing dataset 7
1.4 An example of a short Stata session 9
1.5 Conventions 16
1.6 Chapter summary 17
1.7 Exercises 18
2 Entering data 21
2.1 Creating a dataset 21
2.2 An example questionnaire 23
2.3 Develop a coding system 24
2.4 Kniering data 28
2.4.1 Labeling values 30
2.5 Saving your datasct 34
2.0 Checking the data 35
2.7 Chapter summary 38
2.S Exercises 38
3 Preparing data for analysis 39
3.1 Introduction 39
3.2 Plan your work 39
viii Contents
3.3 Create value labels 44
3.4 Reverse code variables 45
3.5 Create and modify variables 48
3.6 Create scales 53
3.7 Save some of your data 56
3.8 Summary 58
3.9 Exercises 59
4 Working with commands, do files, and results 61
4.1 Introduction 61
4.2 How Stata commands are constructed 62
4.3 Getting the command from the menu system 66
4.4 Saving your results 72
4.5 Logging your command file 73
4.6 Summary 74
4.7 Exercises 75
5 Descriptive statistics and graphs for a single variable 77
5.1 Descriptive statistics and graphs 77
5.2 Where is the center of a distribution? 78
5.3 How dispersed is the distribution? 81
5.4 Statistics and graphs unordered categories 82
5.5 Statistics and graphs ordered categories and variables 88
5.(i Statistics and graphs quantitative variables 90
5.7 Summary 97
5.8 Exercises 98
6 Statistics and graphs for two categorical variables 101
G.I Relationship between categorical variables 101
6.2 Cross tabulation 102
6.3 Chi squared 104
6.3.1 Degrees of freedom¦• optional 106
Contents ix
6.3.2 Probability tables—optional 106
6.4 Percentages and measures of association 109
6.5 Ordered categorical variables 110
6.6 Interactive tables 113
6.7 Tables—linking categorical and quantitative variables 114
6.8 Summary 117
6.9 Exercises 118
7 Tests for one or two means 119
7.1 Tests for one or two means 119
7.2 Randomization 121
7.3 Hypotheses 124
7.4 One sample test of a proportion 124
7.5 Two sample test of a proportion 127
7.6 One sample test of means 131
7.7 Two sample test of group means 133
7.7.1 Testing for unequal variances 138
7.8 Repeated measures t test 139
7.9 Power analysis 111
7.10 Nonparametric alternatives 111
7.10.1 Mann Whitney two sample rank sum tost 111
7.10.2 Nonparainetrie alternative: median test 145
7.11 Summary 115
7.12 Exercises 146
8 Bivariate correlation and regression 149
8.1 Introduction to bivariate correlation and regression 149
8.2 Scattergrams 150
8.3 Plotting the regression line 155
8.4 Correlation 157
8.5 Regression 163
x Contents
8.6 Spearman s rho: rank order correlation for ordinal data 167
8.7 Alpha reliability 168
8.8 Kappa as a measure of agreement for categorical data 173
8.9 Summary 174
8.10 Exercises 175
9 Analysis of variance (ANOVA) 177
9.1 The logic of one way analysis of variance 177
9.2 ANOVA example 178
9.3 ANOVA example using survey data 185
9.4 A nonparametric alternative to ANOVA 188
9.5 Analysis of covariance 191
9.6 Two way ANOVA 198
9.7 Repeated measures design 202
9.8 Intraclass correlation—measuring agreement 207
9.9 Summary 208
9.10 Exercises 209
10 Multiple regression 211
10.1 Introduction 211
10.2 What is multiple regression? 211
10.3 The basic multiple regression command 212
10.4 Increment in R squared: semipartial correlations 216
10.5 Is the dependent variable normally distributed? 218
10.6 An1 the residuals normally distributed? 220
10.7 Regression diagnostic statistics 224
10.7.1 Outliers and influential cases 224
10.7.2 Influential observations: dfbeta 226
10.7.3 Combinations of variables may cause problems 227
10.8 Weighted data 229
10.9 Categorical predictors and hierarchical regression 232
Contents xi
10.10 Fundamentals of interaction 240
10.11 Summary 245
10.12 Exercises 246
11 Logistic regression 249
11.1 Introduction 249
11.2 An example 250
11.3 What are an odds ratio and a logit? 254
11.3.1 The odds ratio 256
11.3.2 The logit transformation 256
11.4 Data used in rest of chapter 257
11.5 Logistic regression 258
11.6 Hypothesis testing 264
11.6.1 Testing individual coefficients 264
11.6.2 Testing sets of coefficients 265
11.7 Nested logistic regressions 267
11.8 Summary 268
11.9 Exercises 270
12 What s next? 271
12.1 Introduction 271
12.2 Resources 271
12.2.1 Web resources 272
12.2.2 Books on Stata 273
12.2.3 Short courses 274
12.2.4 Acquiring data 275
12.3 Summary 276
References 277
Author index 279
Subject index 281
|
| adam_txt |
Contents
Preface xix
Support materials for the book xxi
1 Getting started 1
1.1 Introduction 1
1.2 The Stata screen 3
1.3 Using an existing dataset 7
1.4 An example of a short Stata session 9
1.5 Conventions 16
1.6 Chapter summary 17
1.7 Exercises 18
2 Entering data 21
2.1 Creating a dataset 21
2.2 An example questionnaire 23
2.3 Develop a coding system 24
2.4 Kniering data 28
2.4.1 Labeling values 30
2.5 Saving your datasct 34
2.0 Checking the data 35
2.7 Chapter summary 38
2.S Exercises 38
3 Preparing data for analysis 39
3.1 Introduction 39
3.2 Plan your work 39
viii Contents
3.3 Create value labels 44
3.4 Reverse code variables 45
3.5 Create and modify variables 48
3.6 Create scales 53
3.7 Save some of your data 56
3.8 Summary 58
3.9 Exercises 59
4 Working with commands, do files, and results 61
4.1 Introduction 61
4.2 How Stata commands are constructed 62
4.3 Getting the command from the menu system 66
4.4 Saving your results 72
4.5 Logging your command file 73
4.6 Summary 74
4.7 Exercises 75
5 Descriptive statistics and graphs for a single variable 77
5.1 Descriptive statistics and graphs 77
5.2 Where is the center of a distribution? 78
5.3 How dispersed is the distribution? 81
5.4 Statistics and graphs unordered categories 82
5.5 Statistics and graphs ordered categories and variables 88
5.(i Statistics and graphs quantitative variables 90
5.7 Summary 97
5.8 Exercises 98
6 Statistics and graphs for two categorical variables 101
G.I Relationship between categorical variables 101
6.2 Cross tabulation 102
6.3 Chi squared 104
6.3.1 Degrees of freedom¦• optional 106
Contents ix
6.3.2 Probability tables—optional 106
6.4 Percentages and measures of association 109
6.5 Ordered categorical variables 110
6.6 Interactive tables 113
6.7 Tables—linking categorical and quantitative variables 114
6.8 Summary 117
6.9 Exercises 118
7 Tests for one or two means 119
7.1 Tests for one or two means 119
7.2 Randomization 121
7.3 Hypotheses 124
7.4 One sample test of a proportion 124
7.5 Two sample test of a proportion 127
7.6 One sample test of means 131
7.7 Two sample test of group means 133
7.7.1 Testing for unequal variances 138
7.8 Repeated measures t test 139
7.9 Power analysis 111
7.10 Nonparametric alternatives 111
7.10.1 Mann Whitney two sample rank sum tost 111
7.10.2 Nonparainetrie alternative: median test 145
7.11 Summary 115
7.12 Exercises 146
8 Bivariate correlation and regression 149
8.1 Introduction to bivariate correlation and regression 149
8.2 Scattergrams 150
8.3 Plotting the regression line 155
8.4 Correlation 157
8.5 Regression 163
x Contents
8.6 Spearman's rho: rank order correlation for ordinal data 167
8.7 Alpha reliability 168
8.8 Kappa as a measure of agreement for categorical data 173
8.9 Summary 174
8.10 Exercises 175
9 Analysis of variance (ANOVA) 177
9.1 The logic of one way analysis of variance 177
9.2 ANOVA example 178
9.3 ANOVA example using survey data 185
9.4 A nonparametric alternative to ANOVA 188
9.5 Analysis of covariance 191
9.6 Two way ANOVA 198
9.7 Repeated measures design 202
9.8 Intraclass correlation—measuring agreement 207
9.9 Summary 208
9.10 Exercises 209
10 Multiple regression 211
10.1 Introduction 211
10.2 What is multiple regression? 211
10.3 The basic multiple regression command 212
10.4 Increment in R squared: semipartial correlations 216
10.5 Is the dependent variable normally distributed? 218
10.6 An1 the residuals normally distributed? 220
10.7 Regression diagnostic statistics 224
10.7.1 Outliers and influential cases 224
10.7.2 Influential observations: dfbeta 226
10.7.3 Combinations of variables may cause problems 227
10.8 Weighted data 229
10.9 Categorical predictors and hierarchical regression 232
Contents xi
10.10 Fundamentals of interaction 240
10.11 Summary 245
10.12 Exercises 246
11 Logistic regression 249
11.1 Introduction 249
11.2 An example 250
11.3 What are an odds ratio and a logit? 254
11.3.1 The odds ratio 256
11.3.2 The logit transformation 256
11.4 Data used in rest of chapter 257
11.5 Logistic regression 258
11.6 Hypothesis testing 264
11.6.1 Testing individual coefficients 264
11.6.2 Testing sets of coefficients 265
11.7 Nested logistic regressions 267
11.8 Summary 268
11.9 Exercises 270
12 What's next? 271
12.1 Introduction 271
12.2 Resources 271
12.2.1 Web resources 272
12.2.2 Books on Stata 273
12.2.3 Short courses 274
12.2.4 Acquiring data 275
12.3 Summary 276
References 277
Author index 279
Subject index 281 |
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