Cantitate/Preț
Produs
Total produse
Vezi coșul
Propensity Score Methods and Applications de Haiyan Bai

Propensity Score Methods and Applications: Quantitative Applications in the Social Sciences

Autor Haiyan Bai, M. H. Clark
en Limba Engleză Paperback – 29 dec 2018
A concise, introductory text, Propensity Score Methods and Applications describes propensity score methods (PSM) and how they are used to balance the distributions of observed covariates between treatment conditions as a means to reduce selection bias. This new QASS title specifically focuses on the procedures of implementing PSM for research in social sciences, instead of merely demonstrating the effectiveness of the method.  

Using succinct and approachable language to introduce the basic concepts of PSM, authors Haiyan Bai and M. H. Clark present basic concepts, assumptions, procedures, available software packages, and step-by-step examples for implementing PSM using real-world data, with exercises at the end of each chapter allowing readers to replicate examples on their own.
Citește tot Restrânge

Din seria Quantitative Applications in the Social Sciences

  • Generalized Linear Models for Bounded and Limited Quantitative Variables
    Preț: 31922 lei
  • Approaches to Mixed Methods Research
    Preț: 37289 lei
  • Multidimensional Item Response Theory
    Preț: 37802 lei
  • Gathering Social Network Data
    Preț: 37807 lei
  • Modeling Nonlinearity and Interaction in Regression Analysis Using Spline Variables
    Preț: 37430 lei
  • Applied Bayesian Statistics
    Preț: 37912 lei
  • Confirmatory Factor Analysis
    Preț: 37811 lei
  • Exploring Rating Scale Functioning for Survey Research
    Preț: 37922 lei
  • Sequence Analysis
    Preț: 37972 lei
  • Interpreting and Comparing Effects in Logistic, Probit, and Logit Regression
    Preț: 34832 lei
  • Multilevel Modeling
    Preț: 37776 lei
  • Factorial Survey Experiments
    Preț: 32323 lei
  • Recurrence-Based Analyses
    Preț: 36273 lei
  • Ethnographic Free-List Data
    Preț: 36667 lei
  • Introduction to the Laws of Statistical Sampling
    Preț: 37303 lei
  • Causal Analysis with Panel Data
    Preț: 34140 lei
  • Logistic Regression: A Primer
    Preț: 37839 lei
  • Generalized Linear Models: A Unified Approach
    Preț: 37869 lei
  • Factor Analysis: Statistical Methods and Practical Issues
    Preț: 34119 lei
  • Spatial Regression Models
    Preț: 37809 lei
  • Introduction to the Comparative Method With Boolean Algebra
    Preț: 34182 lei
  • A Mathematical Primer for Social Statistics
    Preț: 37962 lei
  • Fractal Analysis
    Preț: 34151 lei
  • Introduction to Time Series Analysis
    Preț: 37962 lei
  • Linear Regression: A Mathematical Introduction
    Preț: 37747 lei
  • Multilevel Structural Equation Modeling
    Preț: 37839 lei
  • Argument-Based Validation in Testing and Assessment
    Preț: 37864 lei
  • Using Time Series to Analyze Long-Range Fractal Patterns
    Preț: 37777 lei
  • Understanding Correlation Matrices
    Preț: 37777 lei
  • Analyzing Textual Information: From Words to Meanings through Numbers
    Preț: 37900 lei
  • Research Designs
    Preț: 34116 lei
  • Introduction to Survey Sampling
    Preț: 37900 lei
  • Linear Probability, Logit, and Probit Models
    Preț: 34136 lei
  • Randomized Response and Related Methods: Surveying Sensitive Data
    Preț: 37907 lei
  • Regression Diagnostics: An Introduction
    Preț: 37832 lei
  • Time Series Analysis: Regression Techniques
    Preț: 34136 lei
  • Understanding Regression Assumptions
    Preț: 34146 lei
  • Maximum Likelihood Estimation: Logic and Practice
    Preț: 34136 lei
  • nou Analysis of Variance
    Preț: 11420 lei
  • nou Ecological Inference
    Preț: 11420 lei
  • nou Multivariate Tests for Time Series Models
    Preț: 11420 lei
  • nou Interpreting Probability Models: Logit, Probit, and Other Generalized Linear Models
    Preț: 11420 lei
  • nou Typologies and Taxonomies: An Introduction to Classification Techniques
    Preț: 11420 lei
  • Data Analysis: An Introduction
    Preț: 11420 lei
  • Multiple Attribute Decision Making: An Introduction
    Preț: 17573 lei
  • nou Applied Logistic Regression Analysis
    Preț: 11420 lei
  • nou Chaos and Catastrophe Theories
    Preț: 11420 lei

Preț: 37797 lei

Puncte Express: 567

Carte disponibilă

Livrare economică 24 octombrie-07 noiembrie
Livrare express 13-17 octombrie pentru 2388 lei

Livrare prin curier în România Termenul estimat este afișat lângă disponibilitate.
Transport gratuit de la 40000 lei Plată online sau ramburs, în funcție de opțiunile comenzii.
Retur gratuit în 14 zile Comandă securizată și suport în română.
 Adaugă în coș

Wish list
Gift list
Am citit!
Adaugă în listă

Specificații

ISBN-13: 9781506378053
ISBN-10: 1506378056
Pagini: 136
Dimensiuni: 138 x 215 x 7 mm
Greutate: 0.17 kg
Ediția:1
Editura: Sage Publications, Inc
Colecția Quantitative Applications in the Social Sciences
Seria Quantitative Applications in the Social Sciences

Locul publicării:Thousand Oaks, United States

Recenzii

“Haiyan Bai and M.H. Clark have delivered a readable and easily applicable guide for eager researchers with data-in-hand, chomping at the bit to determine whether and how their empirical challenges might be addressed through the careful application of propensity score methods.”
“This volume provides a thorough introduction to propensity score methods while taking care to not overwhelm the reader with dense mathematics. Simple examples, straightforward language, and a catalog of software options make this a fine primer for researchers seeking to incorporate propensity score methods into their own research plans, and an excellent desk reference.”
“This book contains excellent descriptions of propensity score matching with practical examples and clear guides using different software programs.”

Cuprins

Series Editor’s Introduction
About the Authors
Acknowledgments
1. Basic Concepts of Propensity Score Methods
1.1 Causal Inference
1.2 Propensity Scores
1.3 Assumptions
1.4 Summary of the Chapter
2. Covariate Selection and Propensity Score Estimation
2.1 Covariate Selection
2.2 Propensity Score Estimation
2.3 Summary of the Chapter
2.4 An Example
3. Propensity Score Adjustment Methods
3.1 Propensity Score Matching
3.2 Other Propensity Score Adjustment Methods
3.3 Summary of the Chapter
3.4 An Example
4. Covariate Evaluation and Causal Effect Estimation
4.1 Evaluating the Balance of Covariate Distributions
4.2 Causal Effect Estimation
4.3 Sensitivity Analysis
4.4 Summary of the Chapter
4.5 An Example
5. Conclusion
5.1 Limitations of the Propensity Score Methods and How to Address Them
5.2 Summary of Propensity Score Procedures
5.3 Final Comments
References
Index

Notă biografică

Dr. Haiyan Bai is a Professor at the University of Central Florida. She earned her Ph.D. in quantitative research methodology at the University of Cincinnati. Her research interests include issues that revolve around statistical/quantitative methods, specifically, propensity score methods, resampling techniques, research design, measurement, and the application of statistical methods in social and behavioral sciences.

Descriere

A concise, introductory text on propensity score methods that is easy to comprehend by those who have a limited background in statistics, and is practical enough for researchers to quickly generalize and apply the methods.