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->
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Hoboken, N.J., : John Wiley, c2003 | ||
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Lo trovi qui: Univ. Federico II | ||
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Statistical estimation of epidemiological risk [[electronic resource] /] / Kung-Jong Lui |
Autore | Lui Kung-Jong |
Pubbl/distr/stampa | Chichester ; ; Hoboken, NJ, : Wiley, c2004 |
Descrizione fisica | 1 online resource (213 p.) |
Disciplina |
614.4/2/0727
614.4015195 |
Collana | Statistics in practice |
Soggetto topico | Epidemiology - Statistical methods |
Soggetto genere / forma | Electronic books. |
ISBN |
1-280-26954-5
9786610269549 0-470-09407-9 0-470-09408-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Estimation of Epidemiological Risk; Contents; About the author; Preface; 1 Population Proportion or Prevalence; 1.1 Binomial sampling; 1.2 Cluster sampling; 1.3 Inverse sampling; Exercises; References; 2 Risk Difference; 2.1 Independent binomial sampling; 2.2 A series of independent binomial sampling procedures; 2.2.1 Summary interval estimators; 2.2.2 Test for the homogeneity of risk difference; 2.3 Independent cluster sampling; 2.4 Paired-sample data; 2.5 Independent negative binomial sampling (inverse sampling); 2.6 Independent poisson sampling; 2.7 Stratified poisson sampling
ExercisesReferences; 3 Relative Difference; 3.1 Independent binomial sampling; 3.2 A series of independent binomial sampling procedures; 3.2.1 Asymptotic interval estimators; 3.2.2 Test for the homogeneity of relative difference; 3.3 Independent cluster sampling; 3.4 Paired-sample data; 3.5 Independent inverse sampling; Exercises; References; 4 Relative Risk; 4.1 Independent binomial sampling; 4.2 A series of independent binomial sampling procedures; 4.2.1 Asymptotic interval estimators; 4.2.2 Test for the homogeneity of risk ratio; 4.3 Independent cluster sampling; 4.4 Paired-sample data 4.5 Independent inverse sampling4.5.1 Uniformly minimum variance unbiased estimator of relative risk; 4.5.2 Interval estimators of relative risk; 4.6 Independent poisson sampling; 4.7 Stratified poisson sampling; Exercises; References; 5 Odds Ratio; 5.1 Independent binomial sampling; 5.1.1 Asymptotic interval estimators; 5.1.2 Exact confidence interval; 5.2 A series of independent binomial sampling procedures; 5.2.1 Asymptotic interval estimators; 5.2.2 Exact confidence interval; 5.2.3 Test for homogeneity of the odds ratio; 5.3 Independent cluster sampling; 5.4 One-to-one matched sampling 5.5 Logistic modeling5.5.1 Estimation under multinomial or independent binomial sampling; 5.5.2 Estimation in the case of paired-sample data; 5.6 Independent inverse sampling; 5.7 Negative multinomial sampling for paired-sample data; Exercises; References; 6 Generalized Odds Ratio; 6.1 Independent multinomial sampling; 6.2 Data with repeated measurements (or under cluster sampling); 6.3 Paired-sample data; 6.4 Mixed negative multinomial and multinomial sampling; Exercises; References; 7 Attributable Risk; 7.1 Study designs with no confounders; 7.1.1 Cross-sectional sampling 7.1.2 Case-control studies7.2 Study designs with confounders; 7.2.1 Cross-sectional sampling; 7.2.2 Case-control studies; 7.3 Case-control studies with matched pairs; 7.4 Multiple levels of exposure in case-control studies; 7.5 Logistic modeling in case-control studies; 7.5.1 Logistic model containing only the exposure variables of interest; 7.5.2 Logistic regression model containing both exposure and confounding variables; 7.6 Case-control studies under inverse sampling; Exercises; References; 8 Number Needed to Treat; 8.1 Independent binomial sampling 8.2 A series of independent binomial sampling procedures |
Record Nr. | UNINA-9910143227203321 |
Lui Kung-Jong
![]() |
||
Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical estimation of epidemiological risk [[electronic resource] /] / Kung-Jong Lui |
Autore | Lui Kung-Jong |
Pubbl/distr/stampa | Chichester ; ; Hoboken, NJ, : Wiley, c2004 |
Descrizione fisica | 1 online resource (213 p.) |
Disciplina |
614.4/2/0727
614.4015195 |
Collana | Statistics in practice |
Soggetto topico | Epidemiology - Statistical methods |
ISBN |
1-280-26954-5
9786610269549 0-470-09407-9 0-470-09408-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Estimation of Epidemiological Risk; Contents; About the author; Preface; 1 Population Proportion or Prevalence; 1.1 Binomial sampling; 1.2 Cluster sampling; 1.3 Inverse sampling; Exercises; References; 2 Risk Difference; 2.1 Independent binomial sampling; 2.2 A series of independent binomial sampling procedures; 2.2.1 Summary interval estimators; 2.2.2 Test for the homogeneity of risk difference; 2.3 Independent cluster sampling; 2.4 Paired-sample data; 2.5 Independent negative binomial sampling (inverse sampling); 2.6 Independent poisson sampling; 2.7 Stratified poisson sampling
ExercisesReferences; 3 Relative Difference; 3.1 Independent binomial sampling; 3.2 A series of independent binomial sampling procedures; 3.2.1 Asymptotic interval estimators; 3.2.2 Test for the homogeneity of relative difference; 3.3 Independent cluster sampling; 3.4 Paired-sample data; 3.5 Independent inverse sampling; Exercises; References; 4 Relative Risk; 4.1 Independent binomial sampling; 4.2 A series of independent binomial sampling procedures; 4.2.1 Asymptotic interval estimators; 4.2.2 Test for the homogeneity of risk ratio; 4.3 Independent cluster sampling; 4.4 Paired-sample data 4.5 Independent inverse sampling4.5.1 Uniformly minimum variance unbiased estimator of relative risk; 4.5.2 Interval estimators of relative risk; 4.6 Independent poisson sampling; 4.7 Stratified poisson sampling; Exercises; References; 5 Odds Ratio; 5.1 Independent binomial sampling; 5.1.1 Asymptotic interval estimators; 5.1.2 Exact confidence interval; 5.2 A series of independent binomial sampling procedures; 5.2.1 Asymptotic interval estimators; 5.2.2 Exact confidence interval; 5.2.3 Test for homogeneity of the odds ratio; 5.3 Independent cluster sampling; 5.4 One-to-one matched sampling 5.5 Logistic modeling5.5.1 Estimation under multinomial or independent binomial sampling; 5.5.2 Estimation in the case of paired-sample data; 5.6 Independent inverse sampling; 5.7 Negative multinomial sampling for paired-sample data; Exercises; References; 6 Generalized Odds Ratio; 6.1 Independent multinomial sampling; 6.2 Data with repeated measurements (or under cluster sampling); 6.3 Paired-sample data; 6.4 Mixed negative multinomial and multinomial sampling; Exercises; References; 7 Attributable Risk; 7.1 Study designs with no confounders; 7.1.1 Cross-sectional sampling 7.1.2 Case-control studies7.2 Study designs with confounders; 7.2.1 Cross-sectional sampling; 7.2.2 Case-control studies; 7.3 Case-control studies with matched pairs; 7.4 Multiple levels of exposure in case-control studies; 7.5 Logistic modeling in case-control studies; 7.5.1 Logistic model containing only the exposure variables of interest; 7.5.2 Logistic regression model containing both exposure and confounding variables; 7.6 Case-control studies under inverse sampling; Exercises; References; 8 Number Needed to Treat; 8.1 Independent binomial sampling 8.2 A series of independent binomial sampling procedures |
Record Nr. | UNINA-9910830449303321 |
Lui Kung-Jong
![]() |
||
Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
|
Statistical estimation of epidemiological risk / / Kung-Jong Lui |
Autore | Lui Kung-Jong |
Pubbl/distr/stampa | Chichester ; ; Hoboken, NJ, : Wiley, c2004 |
Descrizione fisica | 1 online resource (213 p.) |
Disciplina | 614.4/2/0727 |
Collana | Statistics in practice |
Soggetto topico | Epidemiology - Statistical methods |
ISBN |
1-280-26954-5
9786610269549 0-470-09407-9 0-470-09408-7 |
Formato | Materiale a stampa ![]() |
Livello bibliografico | Monografia |
Lingua di pubblicazione | eng |
Nota di contenuto |
Statistical Estimation of Epidemiological Risk; Contents; About the author; Preface; 1 Population Proportion or Prevalence; 1.1 Binomial sampling; 1.2 Cluster sampling; 1.3 Inverse sampling; Exercises; References; 2 Risk Difference; 2.1 Independent binomial sampling; 2.2 A series of independent binomial sampling procedures; 2.2.1 Summary interval estimators; 2.2.2 Test for the homogeneity of risk difference; 2.3 Independent cluster sampling; 2.4 Paired-sample data; 2.5 Independent negative binomial sampling (inverse sampling); 2.6 Independent poisson sampling; 2.7 Stratified poisson sampling
ExercisesReferences; 3 Relative Difference; 3.1 Independent binomial sampling; 3.2 A series of independent binomial sampling procedures; 3.2.1 Asymptotic interval estimators; 3.2.2 Test for the homogeneity of relative difference; 3.3 Independent cluster sampling; 3.4 Paired-sample data; 3.5 Independent inverse sampling; Exercises; References; 4 Relative Risk; 4.1 Independent binomial sampling; 4.2 A series of independent binomial sampling procedures; 4.2.1 Asymptotic interval estimators; 4.2.2 Test for the homogeneity of risk ratio; 4.3 Independent cluster sampling; 4.4 Paired-sample data 4.5 Independent inverse sampling4.5.1 Uniformly minimum variance unbiased estimator of relative risk; 4.5.2 Interval estimators of relative risk; 4.6 Independent poisson sampling; 4.7 Stratified poisson sampling; Exercises; References; 5 Odds Ratio; 5.1 Independent binomial sampling; 5.1.1 Asymptotic interval estimators; 5.1.2 Exact confidence interval; 5.2 A series of independent binomial sampling procedures; 5.2.1 Asymptotic interval estimators; 5.2.2 Exact confidence interval; 5.2.3 Test for homogeneity of the odds ratio; 5.3 Independent cluster sampling; 5.4 One-to-one matched sampling 5.5 Logistic modeling5.5.1 Estimation under multinomial or independent binomial sampling; 5.5.2 Estimation in the case of paired-sample data; 5.6 Independent inverse sampling; 5.7 Negative multinomial sampling for paired-sample data; Exercises; References; 6 Generalized Odds Ratio; 6.1 Independent multinomial sampling; 6.2 Data with repeated measurements (or under cluster sampling); 6.3 Paired-sample data; 6.4 Mixed negative multinomial and multinomial sampling; Exercises; References; 7 Attributable Risk; 7.1 Study designs with no confounders; 7.1.1 Cross-sectional sampling 7.1.2 Case-control studies7.2 Study designs with confounders; 7.2.1 Cross-sectional sampling; 7.2.2 Case-control studies; 7.3 Case-control studies with matched pairs; 7.4 Multiple levels of exposure in case-control studies; 7.5 Logistic modeling in case-control studies; 7.5.1 Logistic model containing only the exposure variables of interest; 7.5.2 Logistic regression model containing both exposure and confounding variables; 7.6 Case-control studies under inverse sampling; Exercises; References; 8 Number Needed to Treat; 8.1 Independent binomial sampling 8.2 A series of independent binomial sampling procedures |
Record Nr. | UNINA-9910877055803321 |
Lui Kung-Jong
![]() |
||
Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
![]() | ||
Lo trovi qui: Univ. Federico II | ||
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