자료유형  

 학위논문

Control Number  

0016931912

International Standard Book Number  

9798379614737

Dewey Decimal Classification Number  

310

Main Entry-Personal Name  

Che, Jonathan.

Publication, Distribution, etc. (Imprint  

[S.l.] : Harvard University., 2023

Publication, Distribution, etc. (Imprint  

Ann Arbor : ProQuest Dissertations & Theses, 2023

Physical Description  

1 online resource(133 p.)

General Note  

Source: Dissertations Abstracts International, Volume: 84-12, Section: A.

General Note  

Advisor: Miratrix, Luke.

Dissertation Note  

Thesis (Ph.D.)--Harvard University, 2023.

Restrictions on Access Note  

This item must not be sold to any third party vendors.

Summary, Etc.  

요약This thesis presents three self-contained chapters: a dynamic linear model for rating athletes using their game scores (Game), new perspectives power analysis for multisite trials (Site), and a synthetic matching method for observational causal inference (Match).Matching is the most transparent strategy for conducting causal inference with observational data. In Chapter 1, we generalize Coarsened Exact Matching (Iacus et al, 2012) and augment it with local synthetic controls (Abadie et al. 2010). We demonstrate how our method improves performance while preserving the spirit of exact matching, leading to theoretical and practical benefits.Chapter 2 turns to the analysis of game data. Athletic organizations often want to rate athletes' abilities based on their past performances. For sports with multiple competitors in each event, Bayesian dynamic linear models (DLMs) provide a natural framework for doing so. In Chapter 2, we extend DLMs using monotone transformations to account for non-normality in game scores and illustrate the use of our method on Olympic athletes.Multisite trials, where randomized experiments are conducted within each of many sites (e.g., schools), are popular in education. In Chapter 3, we consider the problem of power analysis for these trials. We clarify common misunderstandings in this setting and propose a new approach using average margins of error.

Subject Added Entry-Topical Term  

Statistics.

Subject Added Entry-Topical Term  

Sports management.

Index Term-Uncontrolled  

Games

Index Term-Uncontrolled  

Game scores

Index Term-Uncontrolled  

Match

Index Term-Uncontrolled  

Sports statistics

Added Entry-Corporate Name  

Harvard University Statistics

Host Item Entry  

Dissertations Abstracts International. 84-12A.

Host Item Entry  

Dissertation Abstract International

Electronic Location and Access  

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Control Number  

joongbu:642481