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Advanced Quantitative Techniques in the Social Sciences Ser.: Propensity...
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eBay item number:166741278083
Item specifics
- Condition
- Subject
- Social Sciences
- Level
- Advanced
- ISBN
- 9781452235004
- Publication Name
- Propensity Score Analysis : Statistical Methods and Applications
- Item Length
- 9.4in
- Publisher
- SAGE Publications, Incorporated
- Publication Year
- 2014
- Series
- Advanced Quantitative Techniques in the Social Sciences Ser.
- Type
- Textbook
- Format
- Hardcover
- Language
- English
- Item Height
- 1.1in
- Item Width
- 7.6in
- Item Weight
- 31.4 Oz
- Number of Pages
- 448 Pages
About this product
Product Information
Provides readers with a systematic review of the origins, history, and statistical foundations of Propensity Score Analysis (PSA) and illustrates how it can be used for solving evaluation and causal-inference problems.
Product Identifiers
Publisher
SAGE Publications, Incorporated
ISBN-10
1452235007
ISBN-13
9781452235004
eBay Product ID (ePID)
175761607
Product Key Features
Publication Name
Propensity Score Analysis : Statistical Methods and Applications
Format
Hardcover
Language
English
Publication Year
2014
Series
Advanced Quantitative Techniques in the Social Sciences Ser.
Type
Textbook
Number of Pages
448 Pages
Dimensions
Item Length
9.4in
Item Height
1.1in
Item Width
7.6in
Item Weight
31.4 Oz
Additional Product Features
Series Volume Number
11
Lc Classification Number
Ha29.G91775 2014
Edition Number
2
Reviews
Over the past 35 years, methods of program evaluation have undergone a significant change, and the researchers have recognized the need to develop more efficient approaches for assessing treatment effects from studies based on observational data and for evaluations based on quasi-experimental designs. Written by experts, this volume is updated and fully reflects the current changes to the field. It offers a systematic review of the history, origins, and statistical foundations of propensity score analysis, and more., Over the past 35 years, methods of program evaluation have undergone a significant change, and the researchers have recognized the need to develop more efficient approaches for assessing treatment effects from studies based on observational data and for evaluations based on quasi-experimental designs. Written by experts, this volume is updated and fully reflects the current changes to the field. It offers a systematic review of the history, origins, and statistical foundations of propensity score analysis, and more.
Table of Content
List of TablesList of FiguresPrefaceAbout the AuthorsChapter 1: Introduction Observational Studies History and Development Randomized Experiments Why and When a Propensity Score Analysis Is Needed Computing Software Packages Plan of the BookChapter 2: Counterfactual Framework and Assumptions Causality, Internal Validity, and Threats Counterfactuals and the Neyman-Rubin Counterfactual Framework The Ignorable Treatment Assignment Assumption The Stable Unit Treatment Value Assumption Methods for Estimating Treatment Effects The Underlying Logic of Statistical Inference Types of Treatment Effects Treatment Effect Heterogeneity Heckman's Econometric Model of Causality ConclusionChapter 3: Conventional Methods for Data Balancing Why Is Data Balancing Necessary? A Heuristic Example Three Methods for Data Balancing Design of the Data Simulation Results of the Data Simulation Implications of the Data Simulation Key Issues Regarding the Application of OLS Regression ConclusionChapter 4: Sample Selection and Related Models The Sample Selection Model Treatment Effect Model Overview of the Stata Programs and Main Features of treatreg Examples ConclusionChapter 5: Propensity Score Matching and Related Models Overview The Problem of Dimensionality and the Properties of Propensity Scores Estimating Propensity Scores Matching Postmatching Analysis Propensity Score Matching With Multilevel Data Overview of the Stata and R Programs Examples ConclusionChapter 6: Propensity Score Subclassification Overview The Overlap Assumption and Methods to Address Its Violation Structural Equation Modeling With Propensity Score Subclassification The Stratification-Multilevel Method Examples ConclusionChapter 7: Propensity Score Weighting Overview Weighting Estimators Examples ConclusionChapter 8: Matching Estimators Overview Methods of Matching Estimators Overview of the Stata Program nnmatch Examples ConclusionChapter 9: Propensity Score Analysis With Nonparametric Regression Overview Methods of Propensity Score Analysis With Nonparametric Regression Overview of the Stata Programs psmatch2 and bootstrap Examples ConclusionChapter 10: Propensity Score Analysis of Categorical or Continuous Treatments Overview Modeling Doses With a Single Scalar Balancing Score Estimated by an Ordered Logistic Regression Modeling Doses With Multiple Balancing Scores Estimated by a Multinomial Logit Model The Generalized Propensity Score Estimator Overview of the Stata gpscore Program Examples ConclusionChapter 11: Selection Bias and Sensitivity Analysis Selection Bias: An Overview A Monte Carlo Study Comparing Corrective Models Rosenbaum's Sensitivity Analysis Overview of the Stata Program rbounds Examples ConclusionChapter 12: Concluding Remarks Common Pitfalls in Observational Studies: A Checklist for Critical Review Approximating Experiments With Propensity Score Approaches Other Advances in Modeling Causality Directions for Future DevelopmentReferencesIndex
Copyright Date
2015
Topic
Probability & Statistics / Regression Analysis, Research, Econometrics, Statistics
Lccn
2014-008147
Dewey Decimal
519.5/3
Intended Audience
College Audience
Dewey Edition
22
Illustrated
Yes
Genre
Business & Economics, Mathematics, Social Science
Item description from the seller
Seller assumes all responsibility for this listing.
eBay item number:166741278083
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