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Quantitative methods in population health [[electronic resource] ] : extensions of ordinary regression / / Mari Palta
| Quantitative methods in population health [[electronic resource] ] : extensions of ordinary regression / / Mari Palta |
| Autore | Palta Mari <1948-> |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley, c2003 |
| Descrizione fisica | 1 online resource (339 p.) |
| Disciplina |
614.072
614.420727 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Medical statistics
Regression analysis Population - Health aspects - Statistical methods Health surveys - Statistical methods |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-34400-8
9786610344000 0-470-24688-X 0-471-46798-7 0-471-46797-9 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Quantitative Methods in Population Health; List of Figures; List of Tables; Contents; Preface; Acknowledgments; Acronyms; Introduction; I.1 Newborn Lung Project; I.2 Wisconsin Diabetes Registry; I.3 Wisconsin Sleep Cohort Study; Suggested Reading; 1 Review of Ordinary Linear Regression and Its Assumptions; 1.1 The Ordinary Linear Regression Equation and Its Assumptions; 1.1.1 Straight-Line Relationship; 1.1.2 Equal Variance Assumption; 1.1.3 Normality Assumption; 1.1.4 Independence Assumption; 1.2 A Note on How the Least-Squares Estimators are Obtained
Output Packet I: Examples of Ordinary Regression Analyses2 The Maximum Likelihood Approach to Ordinary Regression; 2.1 Maximum Likelihood Estimation; 2.2 Example; 2.3 Properties of Maximum Likelihood Estimators; 2.4 How to Obtain a Residual Plot with PROC MIXED; Output Packet II: Using PROC MIXED and Comparisons to PROC REG; 3 Reformulating Ordinary Regression Analysis in Matrix Notation; 3.1 Writing the Ordinary Regression Equation in Matrix Notation; 3.1.1 Example; 3.2 Obtaining the Least-Squares Estimator b in Matrix Notation; 3.2.1 Example: Matrices in Regression Analysis 3.3 List of Matrix Operations to Know4 Variance Matrices and Linear Transformations; 4.1 Variance and Correlation Matrices; 4.1.1 Example; 4.2 How to Obtain the Variance of a Linear Transformation; 4.2.1 Two Variables; 4.2.2 Many Variables; 5 Variance Matrices of Estimators of Regression Coefficients; 5.1 Usual Standard Error of Least-Squares Estimator of Regression Slope in Nonmatrix Formulation; 5.2 Standard Errors of Least-Squares Regression Estimators in Matrix Notation; 5.2.1 Example; 5.3 The Large Sample Variance Matrix of Maximum Likelihood Estimators 5.4 Tests and Confidence Intervals5.4.1 Example-Comparing PROC REG and PROC MIXED; 6 Dealing with Unequal Variance Around the Regression Line; 6.1 Ordinary Least Squares with Unequal Variance; 6.1.1 Examples; 6.2 Analysis Taking Unequal Variance into Account; 6.2.1 The Functional Transformation Approach; 6.2.2 The Linear Transformation Approach; 6.2.3 Standard Errors of Weighted Regression Estimators; Output Packet III: Applying the Empirical Option to Adjust Standard Errors; Output Packet IV: Analyses with Transformation of the Outcome Variable to Equalize Residual Variance Output Packet V: Weighted Regression Analyses of GHb Data on Age7 Application of Weighting with Probability Sampling and Nonresponse; 7.1 Sample Surveys with Unequal Probability Sampling; 7.1.1 Example; 7.2 Examining the Impact of Nonresponse; 7.2.1 Example (of Reweighting as Well as Some SAS Manipulations); 7.2.2 A Few Comments on Weighting by a Variable Versus Including it in the Regression Model; Output Packet VI: Survey and Missing Data Weights; 8 Principles in Dealing with Correlated Data; 8.1 Analysis of Correlated Data by Ordinary Unweighted Least-Squares Estimation; 8.1.1 Example 8.1.2 Deriving the Variance Estimator |
| Record Nr. | UNINA-9910143517003321 |
Palta Mari <1948->
|
||
| Hoboken, N.J., : John Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantitative methods in population health [[electronic resource] ] : extensions of ordinary regression / / Mari Palta
| Quantitative methods in population health [[electronic resource] ] : extensions of ordinary regression / / Mari Palta |
| Autore | Palta Mari <1948-> |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley, c2003 |
| Descrizione fisica | 1 online resource (339 p.) |
| Disciplina |
614.072
614.420727 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Medical statistics
Regression analysis Population - Health aspects - Statistical methods Health surveys - Statistical methods |
| ISBN |
1-280-34400-8
9786610344000 0-470-24688-X 0-471-46798-7 0-471-46797-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Quantitative Methods in Population Health; List of Figures; List of Tables; Contents; Preface; Acknowledgments; Acronyms; Introduction; I.1 Newborn Lung Project; I.2 Wisconsin Diabetes Registry; I.3 Wisconsin Sleep Cohort Study; Suggested Reading; 1 Review of Ordinary Linear Regression and Its Assumptions; 1.1 The Ordinary Linear Regression Equation and Its Assumptions; 1.1.1 Straight-Line Relationship; 1.1.2 Equal Variance Assumption; 1.1.3 Normality Assumption; 1.1.4 Independence Assumption; 1.2 A Note on How the Least-Squares Estimators are Obtained
Output Packet I: Examples of Ordinary Regression Analyses2 The Maximum Likelihood Approach to Ordinary Regression; 2.1 Maximum Likelihood Estimation; 2.2 Example; 2.3 Properties of Maximum Likelihood Estimators; 2.4 How to Obtain a Residual Plot with PROC MIXED; Output Packet II: Using PROC MIXED and Comparisons to PROC REG; 3 Reformulating Ordinary Regression Analysis in Matrix Notation; 3.1 Writing the Ordinary Regression Equation in Matrix Notation; 3.1.1 Example; 3.2 Obtaining the Least-Squares Estimator b in Matrix Notation; 3.2.1 Example: Matrices in Regression Analysis 3.3 List of Matrix Operations to Know4 Variance Matrices and Linear Transformations; 4.1 Variance and Correlation Matrices; 4.1.1 Example; 4.2 How to Obtain the Variance of a Linear Transformation; 4.2.1 Two Variables; 4.2.2 Many Variables; 5 Variance Matrices of Estimators of Regression Coefficients; 5.1 Usual Standard Error of Least-Squares Estimator of Regression Slope in Nonmatrix Formulation; 5.2 Standard Errors of Least-Squares Regression Estimators in Matrix Notation; 5.2.1 Example; 5.3 The Large Sample Variance Matrix of Maximum Likelihood Estimators 5.4 Tests and Confidence Intervals5.4.1 Example-Comparing PROC REG and PROC MIXED; 6 Dealing with Unequal Variance Around the Regression Line; 6.1 Ordinary Least Squares with Unequal Variance; 6.1.1 Examples; 6.2 Analysis Taking Unequal Variance into Account; 6.2.1 The Functional Transformation Approach; 6.2.2 The Linear Transformation Approach; 6.2.3 Standard Errors of Weighted Regression Estimators; Output Packet III: Applying the Empirical Option to Adjust Standard Errors; Output Packet IV: Analyses with Transformation of the Outcome Variable to Equalize Residual Variance Output Packet V: Weighted Regression Analyses of GHb Data on Age7 Application of Weighting with Probability Sampling and Nonresponse; 7.1 Sample Surveys with Unequal Probability Sampling; 7.1.1 Example; 7.2 Examining the Impact of Nonresponse; 7.2.1 Example (of Reweighting as Well as Some SAS Manipulations); 7.2.2 A Few Comments on Weighting by a Variable Versus Including it in the Regression Model; Output Packet VI: Survey and Missing Data Weights; 8 Principles in Dealing with Correlated Data; 8.1 Analysis of Correlated Data by Ordinary Unweighted Least-Squares Estimation; 8.1.1 Example 8.1.2 Deriving the Variance Estimator |
| Record Nr. | UNINA-9910830197803321 |
|
Palta Mari <1948->
|
||
| Hoboken, N.J., : John Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Quantitative methods in population health : extensions of ordinary regression / / Mari Palta
| Quantitative methods in population health : extensions of ordinary regression / / Mari Palta |
| Autore | Palta Mari <1948-> |
| Pubbl/distr/stampa | Hoboken, N.J., : John Wiley, c2003 |
| Descrizione fisica | 1 online resource (339 p.) |
| Disciplina | 614.4/2/0727 |
| Collana | Wiley series in probability and statistics |
| Soggetto topico |
Medical statistics
Regression analysis Population - Health aspects - Statistical methods Health surveys - Statistical methods |
| ISBN |
1-280-34400-8
9786610344000 0-470-24688-X 0-471-46798-7 0-471-46797-9 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Quantitative Methods in Population Health; List of Figures; List of Tables; Contents; Preface; Acknowledgments; Acronyms; Introduction; I.1 Newborn Lung Project; I.2 Wisconsin Diabetes Registry; I.3 Wisconsin Sleep Cohort Study; Suggested Reading; 1 Review of Ordinary Linear Regression and Its Assumptions; 1.1 The Ordinary Linear Regression Equation and Its Assumptions; 1.1.1 Straight-Line Relationship; 1.1.2 Equal Variance Assumption; 1.1.3 Normality Assumption; 1.1.4 Independence Assumption; 1.2 A Note on How the Least-Squares Estimators are Obtained
Output Packet I: Examples of Ordinary Regression Analyses2 The Maximum Likelihood Approach to Ordinary Regression; 2.1 Maximum Likelihood Estimation; 2.2 Example; 2.3 Properties of Maximum Likelihood Estimators; 2.4 How to Obtain a Residual Plot with PROC MIXED; Output Packet II: Using PROC MIXED and Comparisons to PROC REG; 3 Reformulating Ordinary Regression Analysis in Matrix Notation; 3.1 Writing the Ordinary Regression Equation in Matrix Notation; 3.1.1 Example; 3.2 Obtaining the Least-Squares Estimator b in Matrix Notation; 3.2.1 Example: Matrices in Regression Analysis 3.3 List of Matrix Operations to Know4 Variance Matrices and Linear Transformations; 4.1 Variance and Correlation Matrices; 4.1.1 Example; 4.2 How to Obtain the Variance of a Linear Transformation; 4.2.1 Two Variables; 4.2.2 Many Variables; 5 Variance Matrices of Estimators of Regression Coefficients; 5.1 Usual Standard Error of Least-Squares Estimator of Regression Slope in Nonmatrix Formulation; 5.2 Standard Errors of Least-Squares Regression Estimators in Matrix Notation; 5.2.1 Example; 5.3 The Large Sample Variance Matrix of Maximum Likelihood Estimators 5.4 Tests and Confidence Intervals5.4.1 Example-Comparing PROC REG and PROC MIXED; 6 Dealing with Unequal Variance Around the Regression Line; 6.1 Ordinary Least Squares with Unequal Variance; 6.1.1 Examples; 6.2 Analysis Taking Unequal Variance into Account; 6.2.1 The Functional Transformation Approach; 6.2.2 The Linear Transformation Approach; 6.2.3 Standard Errors of Weighted Regression Estimators; Output Packet III: Applying the Empirical Option to Adjust Standard Errors; Output Packet IV: Analyses with Transformation of the Outcome Variable to Equalize Residual Variance Output Packet V: Weighted Regression Analyses of GHb Data on Age7 Application of Weighting with Probability Sampling and Nonresponse; 7.1 Sample Surveys with Unequal Probability Sampling; 7.1.1 Example; 7.2 Examining the Impact of Nonresponse; 7.2.1 Example (of Reweighting as Well as Some SAS Manipulations); 7.2.2 A Few Comments on Weighting by a Variable Versus Including it in the Regression Model; Output Packet VI: Survey and Missing Data Weights; 8 Principles in Dealing with Correlated Data; 8.1 Analysis of Correlated Data by Ordinary Unweighted Least-Squares Estimation; 8.1.1 Example 8.1.2 Deriving the Variance Estimator |
| Record Nr. | UNINA-9910876900803321 |
|
Palta Mari <1948->
|
||
| Hoboken, N.J., : John Wiley, c2003 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
