Summary
Instrumental variables (IVs) are used to estimate causal effects on non-experimental observable data.
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IVs are typically used in the equation Y = Xβ + ε.
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The literature on the use of the IVs approach in the educational context includes the most common types of IVs and the guidelines for selecting appropriate variables.
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Empirical examples from the Polish extension of the Programme for International Student Assessment have been used to estimate the effects on student learning outcomes of having at least one neighborhood friend in the classroom.
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Summary
This paper introduces the instrumental-variables (IVs) approach, which is used to estimate causal effects on non-experimental observable data. It reviews the literature on the use of the IVs approach in the educational context, including the most common types of IVs and the guidelines for selecting appropriate variables. It also provides empirical examples that use data from the Polish extension of the Programme for International Student Assessment to estimate the effects on student learning outcomes of having at least one neighborhood friend in the classroom.
Introduction to instrumental variables and their application to large-scale assessment data | Large-scale Assessments in Education | Full Text
springeropen.com
In statistics, econometrics, epidemiology and related disciplines, the method of instrumental variables (IV) is used to estimate causal relationships when controlled experiments are not feasible or when a treatment is not successfully delivered to every unit in a randomized experiment.[1] Intuitively, IVs are used when an explanatory variable of interest is correlated with the error term, in which case ordinary least squares and ANOVA give biased results. A valid instrument induces changes in the explanatory variable but has no independent effect on the dependent variable, allowing a researcher to uncover the causal effect of the explanatory variable on the dependent variable.
Instrumental variables estimation - Wikipedia
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mit.edu
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umanitoba.ca