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Econometric analysis of health data / / edited by Andrew M. Jones and Owen O'Donnell
| Econometric analysis of health data / / edited by Andrew M. Jones and Owen O'Donnell |
| Pubbl/distr/stampa | Chichester, West Sussex, England : , : John Wiley & Sons, Ltd, , 2002 |
| Descrizione fisica | 1 online resource (247 p.) |
| Disciplina |
338.4/33621
614.4015195 |
| Soggetto topico |
Medical statistics - Econometric models
Medical economics - Econometric models Microeconomics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-280-55485-1
9786610554850 0-470-29897-9 0-470-84631-3 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Econometric Analysis of Health Data; Dedication; Contents; List of Contributors; Preface; Introduction; I: Latent Variables and Selection Problems; 1 The demand for health: an empirical reformulation of the Grossman model; 2 Health, health care, and the environment: Econometric evidence from German micro data; 3 Subjective health measures and state-dependent reporting errors; 4 The effect of smoking on health using a sequential self-selection model; II: Count Data and Survival Analysis; 5 A comparison of alternative models of prescription drug utilization
6 Estimates of the use and costs of behavioural health care: a comparison of standard and finite mixture models7 Latent class versus two-part models in the demand for physician services across the European Union; 8 Proportional treatment effects for count response panel data: effects of binary exercise on health care demand; 9 Estimating surgical volume-outcome relationships applying survival models: accounting for frailty and hospital fixed effects; III: Flexible and Semiparametric Estimators; 10 Individual cigarette consumption and addiction: a flexible limited dependent variable approach 11 Identifying demand for health resources using waiting times information12 Non- and semi-parametric estimation of age and time heterogeneity in repeated cross-sections: an application to self-reported morbidity and general practitioner utilization; IV: Classical and Simulation Methods for Panel Data; 13 Unobserved heterogeneity and censoring in the demand for health care; 14 A discrete random effects probit model with application to the demand for preventive care; 15 The use of long-term care services by the Dutch elderly 16 HMO selection and medical care costs: Bayesian MCMC estimation of a robust panel data probit model with survivalIndex |
| Record Nr. | UNINA-9910142531703321 |
| Chichester, West Sussex, England : , : John Wiley & Sons, Ltd, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Econometric analysis of health data / / edited by Andrew M. Jones and Owen O'Donnell
| Econometric analysis of health data / / edited by Andrew M. Jones and Owen O'Donnell |
| Pubbl/distr/stampa | Chichester, West Sussex, England : , : John Wiley & Sons, Ltd, , 2002 |
| Descrizione fisica | 1 online resource (247 p.) |
| Disciplina |
338.4/33621
614.4015195 |
| Soggetto topico |
Medical statistics - Econometric models
Medical economics - Econometric models Microeconomics |
| ISBN |
1-280-55485-1
9786610554850 0-470-29897-9 0-470-84631-3 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Econometric Analysis of Health Data; Dedication; Contents; List of Contributors; Preface; Introduction; I: Latent Variables and Selection Problems; 1 The demand for health: an empirical reformulation of the Grossman model; 2 Health, health care, and the environment: Econometric evidence from German micro data; 3 Subjective health measures and state-dependent reporting errors; 4 The effect of smoking on health using a sequential self-selection model; II: Count Data and Survival Analysis; 5 A comparison of alternative models of prescription drug utilization
6 Estimates of the use and costs of behavioural health care: a comparison of standard and finite mixture models7 Latent class versus two-part models in the demand for physician services across the European Union; 8 Proportional treatment effects for count response panel data: effects of binary exercise on health care demand; 9 Estimating surgical volume-outcome relationships applying survival models: accounting for frailty and hospital fixed effects; III: Flexible and Semiparametric Estimators; 10 Individual cigarette consumption and addiction: a flexible limited dependent variable approach 11 Identifying demand for health resources using waiting times information12 Non- and semi-parametric estimation of age and time heterogeneity in repeated cross-sections: an application to self-reported morbidity and general practitioner utilization; IV: Classical and Simulation Methods for Panel Data; 13 Unobserved heterogeneity and censoring in the demand for health care; 14 A discrete random effects probit model with application to the demand for preventive care; 15 The use of long-term care services by the Dutch elderly 16 HMO selection and medical care costs: Bayesian MCMC estimation of a robust panel data probit model with survivalIndex |
| Record Nr. | UNINA-9910830697803321 |
| Chichester, West Sussex, England : , : John Wiley & Sons, Ltd, , 2002 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical biostatistics for complex diseases [[electronic resource] /] / edited by Frank Emmert-Streib and Matthias Dehmer
| Medical biostatistics for complex diseases [[electronic resource] /] / edited by Frank Emmert-Streib and Matthias Dehmer |
| Pubbl/distr/stampa | Weimheim, : Wiley-VCH, 2010 |
| Descrizione fisica | 1 online resource (413 p.) |
| Disciplina |
610.72721
614.4015195 |
| Altri autori (Persone) |
Emmert-StreibFrank
DehmerMatthias |
| Soggetto topico |
Medicine - Research - Statistical methods
Medical statistics |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-282-68778-6
9786612687785 3-527-63033-3 3-527-63034-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Medical Biostatistics for Complex Diseases; Foreword; Contents; Preface; List of Contributors; Part One: General Biological and Statistical Basics; 1 The Biology of MYC in Health and Disease: A High Altitude View; 1.1 Introduction; 1.2 MYC and Normal Physiology; 1.3 Regulation of Transcription and Gene Expression; 1.4 Metabolism; 1.5 Cell-Cycle Regulation and Differentiation; 1.6 Protein Synthesis; 1.7 Cell Adhesion; 1.8 Apoptosis; 1.9 MicroRNAs; 1.10 Physiological Effects of Loss and Gain of c-myc Function in Mice; 1.10.1 Loss of Function
1.10.2 Gain of Function: Inducible Transgenic Animals1.11 Contributions of MYC to Tumor Biology; 1.12 Introduction of Hematopoietic Malignancies; 1.13 Mechanisms of MYC Dysregulation in Hematological Malignancies; 1.14 Mutation(s) in the MYC Gene in Hematological Cancers; 1.15 Role of MYC in Cell Cycle Regulation and Differentiation in Hematological Cancers; 1.16 Role of BCR Signaling in Conjunction with MYC Overexpression in Lymphoid Malignancies; 1.17 Deregulation of Auxiliary Proteins in Addition to MYC in Hematological Cancers; 1.18 Conclusion; References 2 Cancer Stem Cells - Finding and Capping the Roots of Cancer2.1 Introduction - Stem Cells and Cancer Stem Cells; 2.1.1 What are Stem Cells?; 2.1.2 Concept of Cancer Stem Cells (CSCs); 2.2 Hematopoietic Stem Cells as a Paradigm; 2.2.1 Leukemia as a Paradigmatic Disease for Cancer Research; 2.2.2 CFUs; 2.2.3 LTC-ICs; 2.2.4 In Vivo Repopulation; 2.2.5 Importance of the Bone Marrow Niche; 2.2.6 Leukemic Stem Cells; 2.2.6.1 Leukemic Stem Cells in the Bone Marrow Niche; 2.2.7 CML as a Paradigmatic Entity; 2.3 Current Technical Approach to the Isolation and Characterization of Cancer Stem Cells 2.3.1 Tools for the Detection of Cancer Stem Cells2.3.2 Phenotype of Cancer Stem Cells; 2.4 Cancer Stem Cells in Solid Tumors; 2.4.1 Breast Cancer; 2.4.2 Prostate Cancer; 2.4.3 Colon Cancer; 2.4.4 Other Cancers; 2.5 Open Questions of the Cancer Stem Cell Hypothesis; 2.6 Clinical Relevance of Cancer Stem Cells; 2.6.1 Diagnostic Relevance of Cancer Stem Cells; 2.6.2 Therapeutic Relevance - New Drugs Directed Against Cancer Stem Cells; 2.7 Outlook; References; 3 Multiple Testing Methods; 3.1 Introduction; 3.1.1 A Brief More Focused Introduction; 3.1.2 Historic Development of the Field 3.2 Statistical Background3.2.1 Tests; 3.2.2 Test Statistics and p-Values; 3.2.3 Resampling Based Testing; 3.3 Type I Error Rates; 3.4 Introduction to Multiple Testing Procedures; 3.4.1 Adjusted p-values; 3.4.2 Categories of Multiple Testing Procedures; 3.4.3 Estimation of the Proportion of False Nulls; 3.5 Multiple Testing Procedures; 3.5.1 Procedures Controlling the FWER; 3.5.2 Procedures Controlling the FDR; 3.5.3 Procedures Controlling the FDX Figure; 3.6 Type I Error Rates Control Under Dependence; 3.6.1 FWER Control; 3.6.2 FDR and FDX Control 3.7 Multiple Testing Procedures Applied to Gene Discovery in DNA Microarray Cancer Studies |
| Record Nr. | UNINA-9910140554603321 |
| Weimheim, : Wiley-VCH, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical biostatistics for complex diseases [[electronic resource] /] / edited by Frank Emmert-Streib and Matthias Dehmer
| Medical biostatistics for complex diseases [[electronic resource] /] / edited by Frank Emmert-Streib and Matthias Dehmer |
| Pubbl/distr/stampa | Weimheim, : Wiley-VCH, 2010 |
| Descrizione fisica | 1 online resource (413 p.) |
| Disciplina |
610.72721
614.4015195 |
| Altri autori (Persone) |
Emmert-StreibFrank
DehmerMatthias |
| Soggetto topico |
Medicine - Research - Statistical methods
Medical statistics |
| ISBN |
1-282-68778-6
9786612687785 3-527-63033-3 3-527-63034-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Medical Biostatistics for Complex Diseases; Foreword; Contents; Preface; List of Contributors; Part One: General Biological and Statistical Basics; 1 The Biology of MYC in Health and Disease: A High Altitude View; 1.1 Introduction; 1.2 MYC and Normal Physiology; 1.3 Regulation of Transcription and Gene Expression; 1.4 Metabolism; 1.5 Cell-Cycle Regulation and Differentiation; 1.6 Protein Synthesis; 1.7 Cell Adhesion; 1.8 Apoptosis; 1.9 MicroRNAs; 1.10 Physiological Effects of Loss and Gain of c-myc Function in Mice; 1.10.1 Loss of Function
1.10.2 Gain of Function: Inducible Transgenic Animals1.11 Contributions of MYC to Tumor Biology; 1.12 Introduction of Hematopoietic Malignancies; 1.13 Mechanisms of MYC Dysregulation in Hematological Malignancies; 1.14 Mutation(s) in the MYC Gene in Hematological Cancers; 1.15 Role of MYC in Cell Cycle Regulation and Differentiation in Hematological Cancers; 1.16 Role of BCR Signaling in Conjunction with MYC Overexpression in Lymphoid Malignancies; 1.17 Deregulation of Auxiliary Proteins in Addition to MYC in Hematological Cancers; 1.18 Conclusion; References 2 Cancer Stem Cells - Finding and Capping the Roots of Cancer2.1 Introduction - Stem Cells and Cancer Stem Cells; 2.1.1 What are Stem Cells?; 2.1.2 Concept of Cancer Stem Cells (CSCs); 2.2 Hematopoietic Stem Cells as a Paradigm; 2.2.1 Leukemia as a Paradigmatic Disease for Cancer Research; 2.2.2 CFUs; 2.2.3 LTC-ICs; 2.2.4 In Vivo Repopulation; 2.2.5 Importance of the Bone Marrow Niche; 2.2.6 Leukemic Stem Cells; 2.2.6.1 Leukemic Stem Cells in the Bone Marrow Niche; 2.2.7 CML as a Paradigmatic Entity; 2.3 Current Technical Approach to the Isolation and Characterization of Cancer Stem Cells 2.3.1 Tools for the Detection of Cancer Stem Cells2.3.2 Phenotype of Cancer Stem Cells; 2.4 Cancer Stem Cells in Solid Tumors; 2.4.1 Breast Cancer; 2.4.2 Prostate Cancer; 2.4.3 Colon Cancer; 2.4.4 Other Cancers; 2.5 Open Questions of the Cancer Stem Cell Hypothesis; 2.6 Clinical Relevance of Cancer Stem Cells; 2.6.1 Diagnostic Relevance of Cancer Stem Cells; 2.6.2 Therapeutic Relevance - New Drugs Directed Against Cancer Stem Cells; 2.7 Outlook; References; 3 Multiple Testing Methods; 3.1 Introduction; 3.1.1 A Brief More Focused Introduction; 3.1.2 Historic Development of the Field 3.2 Statistical Background3.2.1 Tests; 3.2.2 Test Statistics and p-Values; 3.2.3 Resampling Based Testing; 3.3 Type I Error Rates; 3.4 Introduction to Multiple Testing Procedures; 3.4.1 Adjusted p-values; 3.4.2 Categories of Multiple Testing Procedures; 3.4.3 Estimation of the Proportion of False Nulls; 3.5 Multiple Testing Procedures; 3.5.1 Procedures Controlling the FWER; 3.5.2 Procedures Controlling the FDR; 3.5.3 Procedures Controlling the FDX Figure; 3.6 Type I Error Rates Control Under Dependence; 3.6.1 FWER Control; 3.6.2 FDR and FDX Control 3.7 Multiple Testing Procedures Applied to Gene Discovery in DNA Microarray Cancer Studies |
| Record Nr. | UNINA-9910830283903321 |
| Weimheim, : Wiley-VCH, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Medical biostatistics for complex diseases / / edited by Frank Emmert-Streib and Matthias Dehmer
| Medical biostatistics for complex diseases / / edited by Frank Emmert-Streib and Matthias Dehmer |
| Pubbl/distr/stampa | Weimheim, : Wiley-VCH, 2010 |
| Descrizione fisica | 1 online resource (413 p.) |
| Disciplina |
610.72721
614.4015195 |
| Altri autori (Persone) |
Emmert-StreibFrank
DehmerMatthias |
| Soggetto topico |
Medicine - Research - Statistical methods
Medical statistics |
| ISBN |
1-282-68778-6
9786612687785 3-527-63033-3 3-527-63034-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Medical Biostatistics for Complex Diseases; Foreword; Contents; Preface; List of Contributors; Part One: General Biological and Statistical Basics; 1 The Biology of MYC in Health and Disease: A High Altitude View; 1.1 Introduction; 1.2 MYC and Normal Physiology; 1.3 Regulation of Transcription and Gene Expression; 1.4 Metabolism; 1.5 Cell-Cycle Regulation and Differentiation; 1.6 Protein Synthesis; 1.7 Cell Adhesion; 1.8 Apoptosis; 1.9 MicroRNAs; 1.10 Physiological Effects of Loss and Gain of c-myc Function in Mice; 1.10.1 Loss of Function
1.10.2 Gain of Function: Inducible Transgenic Animals1.11 Contributions of MYC to Tumor Biology; 1.12 Introduction of Hematopoietic Malignancies; 1.13 Mechanisms of MYC Dysregulation in Hematological Malignancies; 1.14 Mutation(s) in the MYC Gene in Hematological Cancers; 1.15 Role of MYC in Cell Cycle Regulation and Differentiation in Hematological Cancers; 1.16 Role of BCR Signaling in Conjunction with MYC Overexpression in Lymphoid Malignancies; 1.17 Deregulation of Auxiliary Proteins in Addition to MYC in Hematological Cancers; 1.18 Conclusion; References 2 Cancer Stem Cells - Finding and Capping the Roots of Cancer2.1 Introduction - Stem Cells and Cancer Stem Cells; 2.1.1 What are Stem Cells?; 2.1.2 Concept of Cancer Stem Cells (CSCs); 2.2 Hematopoietic Stem Cells as a Paradigm; 2.2.1 Leukemia as a Paradigmatic Disease for Cancer Research; 2.2.2 CFUs; 2.2.3 LTC-ICs; 2.2.4 In Vivo Repopulation; 2.2.5 Importance of the Bone Marrow Niche; 2.2.6 Leukemic Stem Cells; 2.2.6.1 Leukemic Stem Cells in the Bone Marrow Niche; 2.2.7 CML as a Paradigmatic Entity; 2.3 Current Technical Approach to the Isolation and Characterization of Cancer Stem Cells 2.3.1 Tools for the Detection of Cancer Stem Cells2.3.2 Phenotype of Cancer Stem Cells; 2.4 Cancer Stem Cells in Solid Tumors; 2.4.1 Breast Cancer; 2.4.2 Prostate Cancer; 2.4.3 Colon Cancer; 2.4.4 Other Cancers; 2.5 Open Questions of the Cancer Stem Cell Hypothesis; 2.6 Clinical Relevance of Cancer Stem Cells; 2.6.1 Diagnostic Relevance of Cancer Stem Cells; 2.6.2 Therapeutic Relevance - New Drugs Directed Against Cancer Stem Cells; 2.7 Outlook; References; 3 Multiple Testing Methods; 3.1 Introduction; 3.1.1 A Brief More Focused Introduction; 3.1.2 Historic Development of the Field 3.2 Statistical Background3.2.1 Tests; 3.2.2 Test Statistics and p-Values; 3.2.3 Resampling Based Testing; 3.3 Type I Error Rates; 3.4 Introduction to Multiple Testing Procedures; 3.4.1 Adjusted p-values; 3.4.2 Categories of Multiple Testing Procedures; 3.4.3 Estimation of the Proportion of False Nulls; 3.5 Multiple Testing Procedures; 3.5.1 Procedures Controlling the FWER; 3.5.2 Procedures Controlling the FDR; 3.5.3 Procedures Controlling the FDX Figure; 3.6 Type I Error Rates Control Under Dependence; 3.6.1 FWER Control; 3.6.2 FDR and FDX Control 3.7 Multiple Testing Procedures Applied to Gene Discovery in DNA Microarray Cancer Studies |
| Record Nr. | UNINA-9910841545203321 |
| Weimheim, : Wiley-VCH, 2010 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical estimation of epidemiological risk [[electronic resource] /] / Kung-Jong Lui
| 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 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical estimation of epidemiological risk [[electronic resource] /] / Kung-Jong Lui
| 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 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Statistical estimation of epidemiological risk [[electronic resource] /] / Kung-Jong Lui
| 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-9910840753603321 |
|
Lui Kung-Jong
|
||
| Chichester ; ; Hoboken, NJ, : Wiley, c2004 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||