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The Effect "An Introduction to Research Design and Causality"

The Effect "An Introduction to Research Design and Causality"

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  • ISBN:9781032580227
  • Editorial: Crc Press Inc.
  • Fecha de la edición:
  • Número de la edición: 2
  • Encuadernación:
  • Nº Pág.:686
  • Idiomas:Inglés

Materias:

The Effect: An Introduction to Research Design and Causality, Second edition is an excellent teaching text about research design, specifically concerning research that uses observational data to make a causal inference. It is separated into two halves, each with different approaches to that subject. The first half goes through the concepts of causality, with very little in the way of estimation. It introduces the concept of identification thoroughly and clearly and discusses it as a process of trying to isolate variation that has a causal interpretation. Subjects include heavy emphasis on data-generating processes and causal diagrams.

Concepts are demonstrated with a heavy emphasis on graphical intuition and the question of what we do to data. When we 'add a control variable' what does that actually do?

The target audience is practitioners as well as undergraduate and graduate students studying causal inference in various fields such as statistics, econometrics, biostatistics, the social sciences and data science.

Key Features:

Extensive code examples in R, Stata, and Python
Chapters on heterogeneous treatment effects, simulation and power analysis, new cutting-edge methods, and uncomfortable ignored assumptions
An easy-to-read conversational tone
Up-to-date coverage of methods with fast-moving literatures like difference-in-differences
The second edition features a new chapter on partial identification, updated materials, methods, and writing throughout, and additional materials for help navigating the book or in using the book in teaching.

Introduction Finding Stuff in this Book Part I. The Design of Research 1 Designing Research 2 Research Questions 3 Describing Variables 4 Describing Relationships 5 Identification 6 Causal Diagrams 7 Drawing Causal Diagrams 8 Causal Paths and Closing Back Doors 9 Finding Front Doors 10 Treatment Effects 11 Causality with Less Modeling Part II. The Toolbox 12 Opening the Toolbox 13 Regression 14 Matching 15 Simulation 16 Fixed Effects 17 Event Studies 18 Difference-in-Differences 19 Instrumental Variables 20 Regression Discontinuity 21 Partial Identification 22 A Gallery of Rogues: Other Methods 23 Under the Rug Bibliography Index

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