Causal Inference in Educational Research: Approaches, Assumptions and Limitations

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Causal Inference in Educational Research: Approaches, Assumptions and Limitations. / Berger, Stefanie; Hammer, Svenja; Hartmann, Stefan et al.
Mainz: Johannes Gutenberg-Universität Mainz, 2013. (KoKoHs Working Papers; Nr. 4).

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Berger S, Hammer S, Hartmann S, Joachim C, Lösch T. Causal Inference in Educational Research: Approaches, Assumptions and Limitations. Mainz: Johannes Gutenberg-Universität Mainz. 2013. (KoKoHs Working Papers; 4).

Bibtex

@techreport{5da44520fb304c1dabd1c2812167aeea,
title = "Causal Inference in Educational Research: Approaches, Assumptions and Limitations",
abstract = "The Working Paper gives an overview about the topic of causal inference, covered in the Institute on Statistical Analysis for Education Policy organized by the American Educational Research Association in spring 2013. Because randomized experiments are often difficult to implement into large-scale studies in educational research, inference on the causality of different treatments (e.g. different teaching approaches) is limited. This paper discusses the possibilities to draw causal inferences in non-randomized experiments, and provides an introduction to different analytical approaches, namely propensity score analysis, sensitivity analysis and the regression discontinuity approach. The main idea behind each procedure is explained, advantages and limitations are discussed.",
keywords = "Educational science, Casual inference, propensity score, Sensitivity analysis, regression discontinuity",
author = "Stefanie Berger and Svenja Hammer and Stefan Hartmann and Cora Joachim and Thomas L{\"o}sch",
year = "2013",
language = "English",
series = "KoKoHs Working Papers",
publisher = "Johannes Gutenberg-Universit{\"a}t Mainz",
number = "4",
address = "Germany",
type = "WorkingPaper",
institution = "Johannes Gutenberg-Universit{\"a}t Mainz",

}

RIS

TY - UNPB

T1 - Causal Inference in Educational Research

T2 - Approaches, Assumptions and Limitations

AU - Berger, Stefanie

AU - Hammer, Svenja

AU - Hartmann, Stefan

AU - Joachim, Cora

AU - Lösch, Thomas

PY - 2013

Y1 - 2013

N2 - The Working Paper gives an overview about the topic of causal inference, covered in the Institute on Statistical Analysis for Education Policy organized by the American Educational Research Association in spring 2013. Because randomized experiments are often difficult to implement into large-scale studies in educational research, inference on the causality of different treatments (e.g. different teaching approaches) is limited. This paper discusses the possibilities to draw causal inferences in non-randomized experiments, and provides an introduction to different analytical approaches, namely propensity score analysis, sensitivity analysis and the regression discontinuity approach. The main idea behind each procedure is explained, advantages and limitations are discussed.

AB - The Working Paper gives an overview about the topic of causal inference, covered in the Institute on Statistical Analysis for Education Policy organized by the American Educational Research Association in spring 2013. Because randomized experiments are often difficult to implement into large-scale studies in educational research, inference on the causality of different treatments (e.g. different teaching approaches) is limited. This paper discusses the possibilities to draw causal inferences in non-randomized experiments, and provides an introduction to different analytical approaches, namely propensity score analysis, sensitivity analysis and the regression discontinuity approach. The main idea behind each procedure is explained, advantages and limitations are discussed.

KW - Educational science

KW - Casual inference

KW - propensity score

KW - Sensitivity analysis

KW - regression discontinuity

M3 - Working papers

T3 - KoKoHs Working Papers

BT - Causal Inference in Educational Research

PB - Johannes Gutenberg-Universität Mainz

CY - Mainz

ER -

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