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Causality in a social world : moderation, meditation and spill-over / / Guanglei Hong
| Causality in a social world : moderation, meditation and spill-over / / Guanglei Hong |
| Autore | Hong Guanglei |
| Pubbl/distr/stampa | Chichester, England : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (1031 p.) |
| Disciplina | 519.5 |
| Soggetto topico |
Mathematical statistics
Research - Methodology Statistics - Methodology |
| ISBN |
1-119-03063-3
1-119-03060-9 1-119-03064-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Table of Contents; Title page; Preface; Part I: OVERVIEW; 1 Introduction; 1.1 Concepts of moderation, mediation, and spill-over; 1.2 Weighting methods for causal inference; 1.3 Objectives and organization of the book; 1.4 How is this book situated among other publications on related topics?; References; 2 Review of causal inference concepts and methods; 2.1 Causal inference theory; 2.2 Applications to Lord's paradox and Simpson's paradox; 2.3 Identification and estimation; Appendix 2.1: Potential bias in a prima facie effect
Appendix 2.2: Application of the causal inference theory to Lord's paradox References; 3 Review of causal inference designs and analytic methods; 3.1 Experimental designs; 3.2 Quasi-experimental designs; 3.3 Statistical adjustment methods; 3.4 Propensity score; Appendix 3.A: Potential bias due to the omission of treatment-by-covariate interaction; Appendix 3.B: Variable selection for the propensity score model; References; 4 Adjustment for selection bias through weighting; 4.1 Weighted estimation of population parameters in survey sampling 4.2 Weighting adjustment for selection bias in causal inference 4.3 MMWS; Appendix 4.A: Proof of MMWS-adjusted mean observed outcome being unbiased for the population average potential outcome; Appendix 4.B: Derivation of MMWS for estimating the treatment effect on the treated; Appendix 4.C: Theoretical equivalence of MMWS and IPTW; Appendix 4.D: Simulations comparing MMWS and IPTW under misspecifications of the functional form of a propensity score model; References; 5 Evaluations of multivalued treatments; 5.1 Defining the causal effects of multivalued treatments 5.2 Existing designs and analytic methods for evaluating multivalued treatments 5.3 MMWS for evaluating multivalued treatments; 5.4 Summary; Appendix 5.A: Multiple IV for evaluating multivalued treatments; References; Part II: MODERATION; 6 Moderated treatment effects: concepts and existing analytic methods; 6.1 What is moderation?; 6.2 Experimental designs and analytic methods for investigating explicit moderators; 6.3 Existing research designs and analytic methods for investigating implicit moderators Appendix 6.A: Derivation of bias in the fixed-effects estimator when the treatment effect is heterogeneous in multisite randomized trials Appendix 6.B: Derivation of bias in the mixed-effects estimator when the probability of treatment assignment varies across sites; Appendix 6.C: Derivation and proof of the population weight applied to mixed-effects models for eliminating bias in multisite randomized trials; References; 7 Marginal mean weighting through stratification for investigating moderated treatment effects; 7.1 Existing methods for moderation analyses with quasi-experimental data 7.2 MMWS estimation of treatment effects moderated by individual or contextual characteristics |
| Record Nr. | UNINA-9910166637503321 |
Hong Guanglei
|
||
| Chichester, England : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Causality in a social world : moderation, meditation and spill-over / / Guanglei Hong
| Causality in a social world : moderation, meditation and spill-over / / Guanglei Hong |
| Autore | Hong Guanglei |
| Pubbl/distr/stampa | Chichester, England : , : Wiley, , 2015 |
| Descrizione fisica | 1 online resource (1031 p.) |
| Disciplina | 519.5 |
| Soggetto topico |
Mathematical statistics
Research - Methodology Statistics - Methodology |
| ISBN |
1-119-03063-3
1-119-03060-9 1-119-03064-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto |
Cover; Table of Contents; Title page; Preface; Part I: OVERVIEW; 1 Introduction; 1.1 Concepts of moderation, mediation, and spill-over; 1.2 Weighting methods for causal inference; 1.3 Objectives and organization of the book; 1.4 How is this book situated among other publications on related topics?; References; 2 Review of causal inference concepts and methods; 2.1 Causal inference theory; 2.2 Applications to Lord's paradox and Simpson's paradox; 2.3 Identification and estimation; Appendix 2.1: Potential bias in a prima facie effect
Appendix 2.2: Application of the causal inference theory to Lord's paradox References; 3 Review of causal inference designs and analytic methods; 3.1 Experimental designs; 3.2 Quasi-experimental designs; 3.3 Statistical adjustment methods; 3.4 Propensity score; Appendix 3.A: Potential bias due to the omission of treatment-by-covariate interaction; Appendix 3.B: Variable selection for the propensity score model; References; 4 Adjustment for selection bias through weighting; 4.1 Weighted estimation of population parameters in survey sampling 4.2 Weighting adjustment for selection bias in causal inference 4.3 MMWS; Appendix 4.A: Proof of MMWS-adjusted mean observed outcome being unbiased for the population average potential outcome; Appendix 4.B: Derivation of MMWS for estimating the treatment effect on the treated; Appendix 4.C: Theoretical equivalence of MMWS and IPTW; Appendix 4.D: Simulations comparing MMWS and IPTW under misspecifications of the functional form of a propensity score model; References; 5 Evaluations of multivalued treatments; 5.1 Defining the causal effects of multivalued treatments 5.2 Existing designs and analytic methods for evaluating multivalued treatments 5.3 MMWS for evaluating multivalued treatments; 5.4 Summary; Appendix 5.A: Multiple IV for evaluating multivalued treatments; References; Part II: MODERATION; 6 Moderated treatment effects: concepts and existing analytic methods; 6.1 What is moderation?; 6.2 Experimental designs and analytic methods for investigating explicit moderators; 6.3 Existing research designs and analytic methods for investigating implicit moderators Appendix 6.A: Derivation of bias in the fixed-effects estimator when the treatment effect is heterogeneous in multisite randomized trials Appendix 6.B: Derivation of bias in the mixed-effects estimator when the probability of treatment assignment varies across sites; Appendix 6.C: Derivation and proof of the population weight applied to mixed-effects models for eliminating bias in multisite randomized trials; References; 7 Marginal mean weighting through stratification for investigating moderated treatment effects; 7.1 Existing methods for moderation analyses with quasi-experimental data 7.2 MMWS estimation of treatment effects moderated by individual or contextual characteristics |
| Record Nr. | UNINA-9910812455703321 |
|
Hong Guanglei
|
||
| Chichester, England : , : Wiley, , 2015 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||