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Methodological Considerations in Observational Studies of Panel Data: Applications to the Gifted and Talented Program in New York City
Methodological Considerations in Observational Studies of Panel Data: Applications to the Gifted and Talented Program in New York City
상세정보
- 자료유형
- 학위논문 서양
- 최종처리일시
- 20250211151010
- ISBN
- 9798382834467
- DDC
- 151
- 서명/저자
- Methodological Considerations in Observational Studies of Panel Data: Applications to the Gifted and Talented Program in New York City
- 발행사항
- [Sl] : University of Pennsylvania, 2024
- 발행사항
- Ann Arbor : ProQuest Dissertations & Theses, 2024
- 형태사항
- 213 p
- 주기사항
- Source: Dissertations Abstracts International, Volume: 85-12, Section: B.
- 주기사항
- Advisor: Chan, Wendy.
- 학위논문주기
- Thesis (Ph.D.)--University of Pennsylvania, 2024.
- 초록/해제
- 요약Methods to estimate the causal effects of interventions are increasingly used in clinical medicine, public policy and social science. Using observational data, researchers can obtain causal treatment effect estimates without the ethical risks and time constraints that typically burden randomized experiments. The three studies in this dissertation estimate the effects of New York City's Gifted and Talented (G&T) program on academic outcomes using student level data collected between the years 2010 and 2019. Study one evaluates how the synthetic control method performs when estimating the impact of G&T availability on academic outcomes at the sub-district level. Study two estimates the individual average treatment effect through propensity score methods and explores how data augmentation influences the bias and precision of commonly used estimators. The final study uses difference in difference estimation to explore how a city-wide policy impacted the minority representation and academic effectiveness of the G&T program. Given a growing interest in school choice models, these applied analyses are timely. Through simulation and discussion, they also present a critical evaluation of modeling frameworks and research design for causal inference.
- 일반주제명
- Quantitative psychology
- 일반주제명
- Statistics
- 일반주제명
- Education policy
- 일반주제명
- Gifted education
- 키워드
- Causal inference
- 키워드
- Research methods
- 키워드
- Urban education
- 키워드
- New York City
- 기타저자
- University of Pennsylvania Education
- 기본자료저록
- Dissertations Abstracts International. 85-12B.
- 전자적 위치 및 접속
- 로그인 후 원문을 볼 수 있습니다.
MARC
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■020 ▼a9798382834467
■035 ▼a(MiAaPQ)AAI30995421
■040 ▼aMiAaPQ▼cMiAaPQ
■0820 ▼a151
■1001 ▼aWilson, Katherine Jane.
■24510▼aMethodological Considerations in Observational Studies of Panel Data: Applications to the Gifted and Talented Program in New York City
■260 ▼a[Sl]▼bUniversity of Pennsylvania▼c2024
■260 1▼aAnn Arbor▼bProQuest Dissertations & Theses▼c2024
■300 ▼a213 p
■500 ▼aSource: Dissertations Abstracts International, Volume: 85-12, Section: B.
■500 ▼aAdvisor: Chan, Wendy.
■5021 ▼aThesis (Ph.D.)--University of Pennsylvania, 2024.
■520 ▼aMethods to estimate the causal effects of interventions are increasingly used in clinical medicine, public policy and social science. Using observational data, researchers can obtain causal treatment effect estimates without the ethical risks and time constraints that typically burden randomized experiments. The three studies in this dissertation estimate the effects of New York City's Gifted and Talented (G&T) program on academic outcomes using student level data collected between the years 2010 and 2019. Study one evaluates how the synthetic control method performs when estimating the impact of G&T availability on academic outcomes at the sub-district level. Study two estimates the individual average treatment effect through propensity score methods and explores how data augmentation influences the bias and precision of commonly used estimators. The final study uses difference in difference estimation to explore how a city-wide policy impacted the minority representation and academic effectiveness of the G&T program. Given a growing interest in school choice models, these applied analyses are timely. Through simulation and discussion, they also present a critical evaluation of modeling frameworks and research design for causal inference.
■590 ▼aSchool code: 0175.
■650 4▼aQuantitative psychology
■650 4▼aStatistics
■650 4▼aEducation policy
■650 4▼aEducational tests & measurements
■650 4▼aGifted education
■653 ▼aCausal inference
■653 ▼aQuasi-experimental research
■653 ▼aResearch methods
■653 ▼aUrban education
■653 ▼aNew York City
■690 ▼a0632
■690 ▼a0463
■690 ▼a0458
■690 ▼a0445
■690 ▼a0288
■71020▼aUniversity of Pennsylvania▼bEducation.
■7730 ▼tDissertations Abstracts International▼g85-12B.
■790 ▼a0175
■791 ▼aPh.D.
■792 ▼a2024
■793 ▼aEnglish
■85640▼uhttp://www.riss.kr/pdu/ddodLink.do?id=T17160395▼nKERIS▼z이 자료의 원문은 한국교육학술정보원에서 제공합니다.
