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Item response theory / / R. Darrell Bock and Robert D. Gibbons
| Item response theory / / R. Darrell Bock and Robert D. Gibbons |
| Autore | Bock R. Darrell |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2021] |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina | 150.287 |
| Soggetto topico |
Item response theory
Psychology - Mathematical models |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-119-71671-3
1-119-71667-5 1-119-71672-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Record Nr. | UNINA-9910555277603321 |
Bock R. Darrell
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Item response theory / / R. Darrell Bock and Robert D. Gibbons
| Item response theory / / R. Darrell Bock and Robert D. Gibbons |
| Autore | Bock R. Darrell |
| Edizione | [First edition.] |
| Pubbl/distr/stampa | Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2021] |
| Descrizione fisica | 1 online resource (412 pages) |
| Disciplina | 150.287 |
| Soggetto topico |
Item response theory
Psychology - Mathematical models |
| ISBN |
1-119-71671-3
1-119-71667-5 1-119-71672-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
136 3.2.2.8 Illustration 136 3.2.2.9 Rating ScaleModels 136 3.2.3 RankingModel 139 4 Item Parameter Estimation -- Binary Data 141 4.1 Estimation of Item Parameters Assuming Known Attribute Values of the Respondents 142 4.1.1 Estimation 143 4.1.1.1 The 1-parameterModel 143 4.1.1.2 The 2-parameterModel 144 4.1.1.3 The 3-parameterModel 145 4.2 Estimation of Item Parameters Assuming Unknown Attribute Values of the Respondents 146 4.2.1 Joint Maximum Likelihood Estimation (JML) 147 4.2.1.1 The 1-parameter Logistic Model 147 4.2.1.2 Logit-linearAnalysis 148 4.2.1.3 Proportional Marginal Adjustments 153 4.2.2 Marginal Maximum Likelihood Estimation (MML) 158 4.2.2.1 The 2-parameterModel 162 5 Item Parameter Estimation -- Polytomous Data 177 5.1 General Results 177 5.2 The Normal OgiveModel 182 5.3 The NominalCategoriesModel 183 5.4 The Graded
8.2 Computerized Adaptive Testing -- An Overview 244 8.3 Item Selection 245 8.3.1 UnidimensionalComputerized Adaptive Testing (UCAT) 246 8.3.1.1 Fisher Information in IRT Model 246 8.3.1.2 Maximizing Fisher Information (MFI) and Its Limitations 248 8.3.1.3 Modifications toMFI 249 8.3.2 MultidimensionalComputerized Adaptive Testing (MCAT) 251 8.3.2.1 Two Conceptualizations of the Information Function in Multidimensional Space 252 8.3.2.2 SelectionMethods inMCAT 253 8.3.3 Bifactor IRT 256 8.4 Terminating an Adaptive Test 257 8.5 AdditionalConsiderations 258 8.6 An Example fromMental HealthMeasurement 260 8.6.1 The CAT-Mental Health 261 8.6.2 Discussion 264 9 Differential Item Functioning 267 9.1 Introduction 267 9.2 Types of DIF 268 9.3 TheMantel-Haenszel Procedure 270 9.4 Lord'sWald Test 271 9.5 LagrangeMultiplier Test 272 9.6 |
| Record Nr. | UNINA-9910830306503321 |
|
Bock R. Darrell
|
||
| Hoboken, New Jersey : , : John Wiley & Sons, Incorporated, , [2021] | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Longitudinal data analysis [[electronic resource] /] / Donald Hedeker, Robert D. Gibbons
| Longitudinal data analysis [[electronic resource] /] / Donald Hedeker, Robert D. Gibbons |
| Autore | Hedeker Donald R. <1958-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (369 p.) |
| Disciplina |
519.5
610.72/7 |
| Altri autori (Persone) | GibbonsRobert D. <1955-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Longitudinal method
Medicine - Research - Statistical methods Medical sciences - Research - Statistical methods Social sciences - Research - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-44761-3
9786610447619 0-470-03648-6 0-470-03647-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
LONGITUDINAL DATA ANALYSIS; CONTENTS; Preface; Acknowledgments; Acronyms; 1 Introduction; 1.1 Advantages of Longitudinal Studies; 1.2 Challenges of Longitudinal Data Analysis; 1.3 Some General Notation; 1.4 Data Layout; 1.5 Analysis Considerations; 1.6 General Approaches; 1.7 The Simplest Longitudinal Analysis; 1.7.1 Change Score Analysis; 1.7.2 Analysis of Covariance of Post-test Scores; 1.7.3 ANCOVA of Change Scores; 1.7.4 Example; 1.8 Summary; 2 ANOVA Approaches to Longitudinal Data; 2.1 Single-Sample Repeated Measures ANOVA; 2.1.1 Design; 2.1.2 Decomposing the Time Effect
2.1.2.1 Trend Analysis-Orthogonal Polynomial Contrasts2.1.2.2 Change Relative to Baseline-Reference Cell Contrasts; 2.1.2.3 Consecutive Time Comparisons-Profile Contrasts; 2.1.2.4 Contrasting Each Timepoint to the Mean of Subsequent Timepoints-Helmert Contrasts; 2.1.2.5 Contrasting Each Timepoint to the Mean of Others-Deviation Contrasts; 2.1.2.6 Multiple Comparisons; 2.2 Multiple-Sample Repeated Measures ANOVA; 2.2.1 Testing for Group by Time Interaction; 2.2.2 Testing for Subject Effect; 2.2.3 Contrasts for Time Effects; 2.2.3.1 Orthogonal Polynomial Partition of SS 2.2.4 Compound Symmetry and Sphericity2.2.4.1 Sphericity; 2.3 Illustration; 2.4 Summary; 3 MANOVA Approaches to Longitudinal Data; 3.1 Data Layout for ANOVA versus MANOVA; 3.2 MANOVA for Repeated Measurements; 3.2.1 Growth Curve Analysis-Polynomial Representation; 3.2.2 Extracting Univariate Repeated Measures ANOVA Results; 3.2.3 Multivariate Test of the Time Effect; 3.2.4 Tests of Specific Time Elements; 3.3 MANOVA of Repeated Measures-s Sample Case; 3.3.1 Extracting Univariate Repeated Measures ANOVA Results; 3.3.2 Multivariate Tests; 3.4 Illustration; 3.5 Summary 4 Mixed-Effects Regression Models for Continuous Outcomes4.1 Introduction; 4.2 A Simple Linear Regression Model; 4.3 Random Intercept MRM; 4.3.1 Incomplete Data Across Time; 4.3.2 Compound Symmetry and Intraclass Correlation; 4.3.3 Inference; 4.3.4 Psychiatric Dataset; 4.3.5 Random Intercept Model Example; 4.4 Random Intercept and Trend MRM; 4.4.1 Random Intercept and Trend Example; 4.4.2 Coding of Time; 4.4.2.1 Example; 4.4.3 Effect of Diagnosis on Time Trends; 4.5 Matrix Formulation; 4.5.1 Fit of Variance-Covariance Matrix; 4.5.2 Model with Time-Varying Covariates 4.5.2.1 Within and Between-Subjects Effects for Time-Varying Covariates4.5.2.2 Time Interactions with Time-Varying Covariates; 4.6 Estimation; 4.6.1 ML Bias in Estimation of Variance Parameters; 4.7 Summary; 5 Mixed-Effects Polynomial Regression Models; 5.1 Introduction; 5.2 Curvilinear Trend Model; 5.2.1 Curvilinear Trend Example; 5.3 Orthogonal Polynomials; 5.3.1 Model Representations; 5.3.2 Orthogonal Polynomial Trend Example; 5.3.3 Translating Parameters; 5.3.4 Higher-Order Polynomial Models; 5.3.5 Cubic Trend Example; 5.4 Summary; 6 Covariance Pattern Models; 6.1 Introduction 6.2 Covariance Pattern Models |
| Record Nr. | UNINA-9910143573903321 |
|
Hedeker Donald R. <1958->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Longitudinal data analysis [[electronic resource] /] / Donald Hedeker, Robert D. Gibbons
| Longitudinal data analysis [[electronic resource] /] / Donald Hedeker, Robert D. Gibbons |
| Autore | Hedeker Donald R. <1958-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (369 p.) |
| Disciplina |
519.5
610.72/7 |
| Altri autori (Persone) | GibbonsRobert D. <1955-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Longitudinal method
Medicine - Research - Statistical methods Medical sciences - Research - Statistical methods Social sciences - Research - Statistical methods |
| ISBN |
1-280-44761-3
9786610447619 0-470-03648-6 0-470-03647-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
LONGITUDINAL DATA ANALYSIS; CONTENTS; Preface; Acknowledgments; Acronyms; 1 Introduction; 1.1 Advantages of Longitudinal Studies; 1.2 Challenges of Longitudinal Data Analysis; 1.3 Some General Notation; 1.4 Data Layout; 1.5 Analysis Considerations; 1.6 General Approaches; 1.7 The Simplest Longitudinal Analysis; 1.7.1 Change Score Analysis; 1.7.2 Analysis of Covariance of Post-test Scores; 1.7.3 ANCOVA of Change Scores; 1.7.4 Example; 1.8 Summary; 2 ANOVA Approaches to Longitudinal Data; 2.1 Single-Sample Repeated Measures ANOVA; 2.1.1 Design; 2.1.2 Decomposing the Time Effect
2.1.2.1 Trend Analysis-Orthogonal Polynomial Contrasts2.1.2.2 Change Relative to Baseline-Reference Cell Contrasts; 2.1.2.3 Consecutive Time Comparisons-Profile Contrasts; 2.1.2.4 Contrasting Each Timepoint to the Mean of Subsequent Timepoints-Helmert Contrasts; 2.1.2.5 Contrasting Each Timepoint to the Mean of Others-Deviation Contrasts; 2.1.2.6 Multiple Comparisons; 2.2 Multiple-Sample Repeated Measures ANOVA; 2.2.1 Testing for Group by Time Interaction; 2.2.2 Testing for Subject Effect; 2.2.3 Contrasts for Time Effects; 2.2.3.1 Orthogonal Polynomial Partition of SS 2.2.4 Compound Symmetry and Sphericity2.2.4.1 Sphericity; 2.3 Illustration; 2.4 Summary; 3 MANOVA Approaches to Longitudinal Data; 3.1 Data Layout for ANOVA versus MANOVA; 3.2 MANOVA for Repeated Measurements; 3.2.1 Growth Curve Analysis-Polynomial Representation; 3.2.2 Extracting Univariate Repeated Measures ANOVA Results; 3.2.3 Multivariate Test of the Time Effect; 3.2.4 Tests of Specific Time Elements; 3.3 MANOVA of Repeated Measures-s Sample Case; 3.3.1 Extracting Univariate Repeated Measures ANOVA Results; 3.3.2 Multivariate Tests; 3.4 Illustration; 3.5 Summary 4 Mixed-Effects Regression Models for Continuous Outcomes4.1 Introduction; 4.2 A Simple Linear Regression Model; 4.3 Random Intercept MRM; 4.3.1 Incomplete Data Across Time; 4.3.2 Compound Symmetry and Intraclass Correlation; 4.3.3 Inference; 4.3.4 Psychiatric Dataset; 4.3.5 Random Intercept Model Example; 4.4 Random Intercept and Trend MRM; 4.4.1 Random Intercept and Trend Example; 4.4.2 Coding of Time; 4.4.2.1 Example; 4.4.3 Effect of Diagnosis on Time Trends; 4.5 Matrix Formulation; 4.5.1 Fit of Variance-Covariance Matrix; 4.5.2 Model with Time-Varying Covariates 4.5.2.1 Within and Between-Subjects Effects for Time-Varying Covariates4.5.2.2 Time Interactions with Time-Varying Covariates; 4.6 Estimation; 4.6.1 ML Bias in Estimation of Variance Parameters; 4.7 Summary; 5 Mixed-Effects Polynomial Regression Models; 5.1 Introduction; 5.2 Curvilinear Trend Model; 5.2.1 Curvilinear Trend Example; 5.3 Orthogonal Polynomials; 5.3.1 Model Representations; 5.3.2 Orthogonal Polynomial Trend Example; 5.3.3 Translating Parameters; 5.3.4 Higher-Order Polynomial Models; 5.3.5 Cubic Trend Example; 5.4 Summary; 6 Covariance Pattern Models; 6.1 Introduction 6.2 Covariance Pattern Models |
| Record Nr. | UNINA-9910830719503321 |
|
Hedeker Donald R. <1958->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Longitudinal data analysis / / Donald Hedeker, Robert D. Gibbons
| Longitudinal data analysis / / Donald Hedeker, Robert D. Gibbons |
| Autore | Hedeker Donald R. <1958-> |
| Pubbl/distr/stampa | Hoboken, N.J., : Wiley-Interscience, c2006 |
| Descrizione fisica | 1 online resource (369 p.) |
| Disciplina | 610.72/7 |
| Altri autori (Persone) | GibbonsRobert D. <1955-> |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Longitudinal method
Medicine - Research - Statistical methods Medical sciences - Research - Statistical methods Social sciences - Research - Statistical methods |
| ISBN |
1-280-44761-3
9786610447619 0-470-03648-6 0-470-03647-8 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
LONGITUDINAL DATA ANALYSIS; CONTENTS; Preface; Acknowledgments; Acronyms; 1 Introduction; 1.1 Advantages of Longitudinal Studies; 1.2 Challenges of Longitudinal Data Analysis; 1.3 Some General Notation; 1.4 Data Layout; 1.5 Analysis Considerations; 1.6 General Approaches; 1.7 The Simplest Longitudinal Analysis; 1.7.1 Change Score Analysis; 1.7.2 Analysis of Covariance of Post-test Scores; 1.7.3 ANCOVA of Change Scores; 1.7.4 Example; 1.8 Summary; 2 ANOVA Approaches to Longitudinal Data; 2.1 Single-Sample Repeated Measures ANOVA; 2.1.1 Design; 2.1.2 Decomposing the Time Effect
2.1.2.1 Trend Analysis-Orthogonal Polynomial Contrasts2.1.2.2 Change Relative to Baseline-Reference Cell Contrasts; 2.1.2.3 Consecutive Time Comparisons-Profile Contrasts; 2.1.2.4 Contrasting Each Timepoint to the Mean of Subsequent Timepoints-Helmert Contrasts; 2.1.2.5 Contrasting Each Timepoint to the Mean of Others-Deviation Contrasts; 2.1.2.6 Multiple Comparisons; 2.2 Multiple-Sample Repeated Measures ANOVA; 2.2.1 Testing for Group by Time Interaction; 2.2.2 Testing for Subject Effect; 2.2.3 Contrasts for Time Effects; 2.2.3.1 Orthogonal Polynomial Partition of SS 2.2.4 Compound Symmetry and Sphericity2.2.4.1 Sphericity; 2.3 Illustration; 2.4 Summary; 3 MANOVA Approaches to Longitudinal Data; 3.1 Data Layout for ANOVA versus MANOVA; 3.2 MANOVA for Repeated Measurements; 3.2.1 Growth Curve Analysis-Polynomial Representation; 3.2.2 Extracting Univariate Repeated Measures ANOVA Results; 3.2.3 Multivariate Test of the Time Effect; 3.2.4 Tests of Specific Time Elements; 3.3 MANOVA of Repeated Measures-s Sample Case; 3.3.1 Extracting Univariate Repeated Measures ANOVA Results; 3.3.2 Multivariate Tests; 3.4 Illustration; 3.5 Summary 4 Mixed-Effects Regression Models for Continuous Outcomes4.1 Introduction; 4.2 A Simple Linear Regression Model; 4.3 Random Intercept MRM; 4.3.1 Incomplete Data Across Time; 4.3.2 Compound Symmetry and Intraclass Correlation; 4.3.3 Inference; 4.3.4 Psychiatric Dataset; 4.3.5 Random Intercept Model Example; 4.4 Random Intercept and Trend MRM; 4.4.1 Random Intercept and Trend Example; 4.4.2 Coding of Time; 4.4.2.1 Example; 4.4.3 Effect of Diagnosis on Time Trends; 4.5 Matrix Formulation; 4.5.1 Fit of Variance-Covariance Matrix; 4.5.2 Model with Time-Varying Covariates 4.5.2.1 Within and Between-Subjects Effects for Time-Varying Covariates4.5.2.2 Time Interactions with Time-Varying Covariates; 4.6 Estimation; 4.6.1 ML Bias in Estimation of Variance Parameters; 4.7 Summary; 5 Mixed-Effects Polynomial Regression Models; 5.1 Introduction; 5.2 Curvilinear Trend Model; 5.2.1 Curvilinear Trend Example; 5.3 Orthogonal Polynomials; 5.3.1 Model Representations; 5.3.2 Orthogonal Polynomial Trend Example; 5.3.3 Translating Parameters; 5.3.4 Higher-Order Polynomial Models; 5.3.5 Cubic Trend Example; 5.4 Summary; 6 Covariance Pattern Models; 6.1 Introduction 6.2 Covariance Pattern Models |
| Record Nr. | UNINA-9910877657203321 |
|
Hedeker Donald R. <1958->
|
||
| Hoboken, N.J., : Wiley-Interscience, c2006 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||