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Statistical power analysis with missing data : a structural equation modeling approach / / Adam Davey, Jyoti Savla
| Statistical power analysis with missing data : a structural equation modeling approach / / Adam Davey, Jyoti Savla |
| Autore | Davey Adam |
| Pubbl/distr/stampa | New York : , : Routledge, , 2010 |
| Descrizione fisica | 1 online resource (370 p.) |
| Disciplina |
001.422
519.5 |
| Altri autori (Persone) | SavlaJyoti |
| Soggetto topico |
Social sciences
Social sciences - Statistical methods Social sciences - Mathematical models |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-135-26931-9
1-282-29455-5 9786612294556 0-203-86695-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Statistical Power Analysis with Missing Data; Copyright Page; Contents; 1. Introduction; Overview and Aims; Statistical Power; Testing Hypotheses; Choosing an Alternative Hypothesis; Central and Noncentral Distributions; Factors Important for Power; Effect Sizes; Determining an Effect Size; Point Estimates and Confidence Intervals; Reasons to Estimate Statistical Power; Conclusions; Further Readings; Section I: Fundamentals; 2. The LISREL Model; Matrices and the LISREL Model; Latent and Manifest Variables; Regression Coefficient Matrices; Variance-Covariance Matrices
Vectors of Means and InterceptsModel Parameters; Models and Matrices; Structure of a LISREL Program; Reading and Interpreting LISREL Output; Evaluating Model Fit; Measures of Population Discrepancy; Incremental Fit Indices; Absolute Fit Indices; Conclusions; Further Readings; 3. Missing Data: An Overview; Why Worry About Missing Data?; Types of Missing Data; Missing Completely at Random; Missing at Random; Missing Not at Random; Strategies for Dealing With Missing Data; Complete Case Methods; List-Wise Deletion; List-Wise Deletion With Weighting; Available Case Methods; Pair-Wise Deletion Expectation Maximization AlgorithmFull Information Maximum Likelihood; Imputation Methods; Single Imputation; Multiple Imputation; Estimating Structural Equation Models With Incomplete Data; Conclusions; Further Readings; 4. Estimating Statistical Power With Complete Data; Statistical Power in Structural Equation Modeling; Power for Testing a Single Alternative Hypothesis; Tests of Exact, Close, and Not Close Fit; Tests of Exact, Close, and Not Close Fit Between Two Models; An Alternative Approach to Estimate Statistical Power; Estimating Required Sample Size for Given Power; Conclusions Further ReadingsSection II: Applications; 5. Effects of Selection on Means, Variances, and Covariances; Defining the Population Model; Defining the Selection Process; An Example of the Effects of Selection; Selecting Data Into More Than Two Groups; Conclusions; Further Readings; 6. Testing Covariances and Mean Differences With Missing Data; Step 1: Specifying the Population Model; Step 2: Specifying the Alternative Model; Step 3: Generate Data Structure Implied by the Population Model; Step 4: Decide on the Incomplete Data Model; Step 5: Apply the Incomplete Data Model to Population Data Step 6: Estimate Population and Alternative Models With Missing DataStep 7: Using the Results to Estimate Power or Required Sample Size; Conclusions; Further Readings; 7. Testing Group Differences in Longitudinal Change; The Application; The Steps; Step 1: Selecting a Population Model; Step 2: Selecting an Alternative Model; Step 3: Generating Data According to the Population Model; Step 4: Selecting a Missing Data Model; Step 5: Applying the Missing Data Model to Population Data; Step 6: Estimating Population and Alternative Models With Incomplete Data Step 7: Using the Results to Calculate Power or Required Sample Size |
| Record Nr. | UNINA-9910455417703321 |
Davey Adam
|
||
| New York : , : Routledge, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical power analysis with missing data : a structural equation modeling approach / / Adam Davey, Jyoti Savla
| Statistical power analysis with missing data : a structural equation modeling approach / / Adam Davey, Jyoti Savla |
| Autore | Davey Adam |
| Pubbl/distr/stampa | New York : , : Routledge, , 2010 |
| Descrizione fisica | 1 online resource (370 p.) |
| Disciplina |
001.422
519.5 |
| Altri autori (Persone) | SavlaJyoti |
| Soggetto topico |
Social sciences
Social sciences - Statistical methods Social sciences - Mathematical models |
| ISBN |
1-135-26930-0
1-135-26931-9 1-282-29455-5 9786612294556 0-203-86695-9 |
| Classificazione | QH 234 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Statistical Power Analysis with Missing Data; Copyright Page; Contents; 1. Introduction; Overview and Aims; Statistical Power; Testing Hypotheses; Choosing an Alternative Hypothesis; Central and Noncentral Distributions; Factors Important for Power; Effect Sizes; Determining an Effect Size; Point Estimates and Confidence Intervals; Reasons to Estimate Statistical Power; Conclusions; Further Readings; Section I: Fundamentals; 2. The LISREL Model; Matrices and the LISREL Model; Latent and Manifest Variables; Regression Coefficient Matrices; Variance-Covariance Matrices
Vectors of Means and InterceptsModel Parameters; Models and Matrices; Structure of a LISREL Program; Reading and Interpreting LISREL Output; Evaluating Model Fit; Measures of Population Discrepancy; Incremental Fit Indices; Absolute Fit Indices; Conclusions; Further Readings; 3. Missing Data: An Overview; Why Worry About Missing Data?; Types of Missing Data; Missing Completely at Random; Missing at Random; Missing Not at Random; Strategies for Dealing With Missing Data; Complete Case Methods; List-Wise Deletion; List-Wise Deletion With Weighting; Available Case Methods; Pair-Wise Deletion Expectation Maximization AlgorithmFull Information Maximum Likelihood; Imputation Methods; Single Imputation; Multiple Imputation; Estimating Structural Equation Models With Incomplete Data; Conclusions; Further Readings; 4. Estimating Statistical Power With Complete Data; Statistical Power in Structural Equation Modeling; Power for Testing a Single Alternative Hypothesis; Tests of Exact, Close, and Not Close Fit; Tests of Exact, Close, and Not Close Fit Between Two Models; An Alternative Approach to Estimate Statistical Power; Estimating Required Sample Size for Given Power; Conclusions Further ReadingsSection II: Applications; 5. Effects of Selection on Means, Variances, and Covariances; Defining the Population Model; Defining the Selection Process; An Example of the Effects of Selection; Selecting Data Into More Than Two Groups; Conclusions; Further Readings; 6. Testing Covariances and Mean Differences With Missing Data; Step 1: Specifying the Population Model; Step 2: Specifying the Alternative Model; Step 3: Generate Data Structure Implied by the Population Model; Step 4: Decide on the Incomplete Data Model; Step 5: Apply the Incomplete Data Model to Population Data Step 6: Estimate Population and Alternative Models With Missing DataStep 7: Using the Results to Estimate Power or Required Sample Size; Conclusions; Further Readings; 7. Testing Group Differences in Longitudinal Change; The Application; The Steps; Step 1: Selecting a Population Model; Step 2: Selecting an Alternative Model; Step 3: Generating Data According to the Population Model; Step 4: Selecting a Missing Data Model; Step 5: Applying the Missing Data Model to Population Data; Step 6: Estimating Population and Alternative Models With Incomplete Data Step 7: Using the Results to Calculate Power or Required Sample Size |
| Record Nr. | UNINA-9910778573303321 |
|
Davey Adam
|
||
| New York : , : Routledge, , 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical power analysis with missing data : a structural equation modeling approach / / Adam Davey, Jyoti Savla
| Statistical power analysis with missing data : a structural equation modeling approach / / Adam Davey, Jyoti Savla |
| Autore | Davey Adam |
| Edizione | [1st ed.] |
| Pubbl/distr/stampa | New York, : Routledge, c2010 |
| Descrizione fisica | 1 online resource (370 p.) |
| Disciplina |
001.422
519.5 |
| Altri autori (Persone) | SavlaJyoti |
| Soggetto topico |
Social sciences
Social sciences - Statistical methods Social sciences - Mathematical models |
| ISBN |
1-135-26930-0
1-135-26931-9 1-282-29455-5 9786612294556 0-203-86695-9 |
| Classificazione | QH 234 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Front Cover; Statistical Power Analysis with Missing Data; Copyright Page; Contents; 1. Introduction; Overview and Aims; Statistical Power; Testing Hypotheses; Choosing an Alternative Hypothesis; Central and Noncentral Distributions; Factors Important for Power; Effect Sizes; Determining an Effect Size; Point Estimates and Confidence Intervals; Reasons to Estimate Statistical Power; Conclusions; Further Readings; Section I: Fundamentals; 2. The LISREL Model; Matrices and the LISREL Model; Latent and Manifest Variables; Regression Coefficient Matrices; Variance-Covariance Matrices
Vectors of Means and InterceptsModel Parameters; Models and Matrices; Structure of a LISREL Program; Reading and Interpreting LISREL Output; Evaluating Model Fit; Measures of Population Discrepancy; Incremental Fit Indices; Absolute Fit Indices; Conclusions; Further Readings; 3. Missing Data: An Overview; Why Worry About Missing Data?; Types of Missing Data; Missing Completely at Random; Missing at Random; Missing Not at Random; Strategies for Dealing With Missing Data; Complete Case Methods; List-Wise Deletion; List-Wise Deletion With Weighting; Available Case Methods; Pair-Wise Deletion Expectation Maximization AlgorithmFull Information Maximum Likelihood; Imputation Methods; Single Imputation; Multiple Imputation; Estimating Structural Equation Models With Incomplete Data; Conclusions; Further Readings; 4. Estimating Statistical Power With Complete Data; Statistical Power in Structural Equation Modeling; Power for Testing a Single Alternative Hypothesis; Tests of Exact, Close, and Not Close Fit; Tests of Exact, Close, and Not Close Fit Between Two Models; An Alternative Approach to Estimate Statistical Power; Estimating Required Sample Size for Given Power; Conclusions Further ReadingsSection II: Applications; 5. Effects of Selection on Means, Variances, and Covariances; Defining the Population Model; Defining the Selection Process; An Example of the Effects of Selection; Selecting Data Into More Than Two Groups; Conclusions; Further Readings; 6. Testing Covariances and Mean Differences With Missing Data; Step 1: Specifying the Population Model; Step 2: Specifying the Alternative Model; Step 3: Generate Data Structure Implied by the Population Model; Step 4: Decide on the Incomplete Data Model; Step 5: Apply the Incomplete Data Model to Population Data Step 6: Estimate Population and Alternative Models With Missing DataStep 7: Using the Results to Estimate Power or Required Sample Size; Conclusions; Further Readings; 7. Testing Group Differences in Longitudinal Change; The Application; The Steps; Step 1: Selecting a Population Model; Step 2: Selecting an Alternative Model; Step 3: Generating Data According to the Population Model; Step 4: Selecting a Missing Data Model; Step 5: Applying the Missing Data Model to Population Data; Step 6: Estimating Population and Alternative Models With Incomplete Data Step 7: Using the Results to Calculate Power or Required Sample Size |
| Record Nr. | UNINA-9910954298403321 |
|
Davey Adam
|
||
| New York, : Routledge, c2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||