Understanding Counterfactuals and the Potential Outcomes Framework

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Questions and Answers

How is a counterfactual related to causal inference?

  • It allows researchers to estimate the causal effect of a treatment or intervention (correct)
  • It helps in identifying correlations between variables
  • It provides the statistical variance of the data
  • It is used to calculate the mean effect size in a study

What characterizes a counterfactual outcome in the context of the Rubin Causal Model?

  • It is the outcome that would have been observed if a unit received a different treatment (correct)
  • It is the least likely outcome predicted by the model
  • It is an outcome that has no relation to treatment effects
  • It is the most common outcome observed in a study

Why are counterfactuals important in various fields such as history and social sciences?

  • To quantify the direct effects of variables on outcomes
  • To provide accurate predictions about future events
  • To analyze what could have happened if past events unfolded differently (correct)
  • To simplify complex data analysis processes

What are the things you want to explain or predict in a regression analysis?

<p>Dependent variables (A)</p> Signup and view all the answers

In regression equations, what does the term 'β' represent in econometrics notation?

<p>Coefficient for the causal effect (C)</p> Signup and view all the answers

Which statistical method is used to estimate unobservable counterfactual outcomes?

<p>Propensity score matching (C)</p> Signup and view all the answers

What do sliders represent as metaphors for regression coefficients?

<p>Continuous variables that show the causal effect (C)</p> Signup and view all the answers

Which variables are manipulated or observed to see their effect on the outcome variable in a study?

<p>Independent variables (A)</p> Signup and view all the answers

What does '0' represent in the statistical flavor notation of a regression equation?

<p>Y-intercept of the regression line (A)</p> Signup and view all the answers

Flashcards

Counterfactual outcome

The outcome that would have been observed if a unit received a different treatment, according to the Rubin Causal Model.

Causal inference

Estimating the effect of a treatment or intervention using counterfactuals.

Regression analysis dependent variable

The variable you want to explain or predict in regression analysis.

Regression coefficient (β)

The causal effect in a regression equation, showing how much a dependent variable changes with each unit change in the independent variable.

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Propensity score matching

A statistical method for estimating unobservable counterfactual outcomes.

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Regression coefficient sliders

Continuous variables in regression analysis representing the causal effect.

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Independent variables

Variables manipulated or observed to see their effect on the outcome variable.

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Regression Y-intercept

The value of the dependent variable when all independent variables are equal to 0 in a regression equation.

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Counterfactual in history/social sciences

Analyzing 'what if' scenarios in past events to understand potential alternative outcomes.

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