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A General Approach to Causal Mediation Analysis
The approach is general because it offers the definition, identification, estimation, and sensitivity analysis of causal mediation effects without reference to any specific statistical model and can accommodate linear and nonlinear relationships, parametric and nonparametric models, continuous and discrete mediators, and various types of outcome variables.
Structural Topic Models for Open‐Ended Survey Responses
The structural topic model makes analyzing open-ended responses easier, more revealing, and capable of being used to estimate treatment effects, and is illustrated with analysis of text from surveys and experiments.
Redefine statistical significance
The default P-value threshold for statistical significance is proposed to be changed from 0.05 to 0.005 for claims of new discoveries in order to reduce uncertainty in the number of discoveries.
Unpacking the Black Box of Causality: Learning about Causal Mechanisms from Experimental and Observational Studies
This work presents a minimum set of assumptions required under standard designs of experimental and observational studies and develops a general algorithm for estimating causal mediation effects and provides a method for assessing the sensitivity of conclusions to potential violations of a key assumption.
stm: An R Package for Structural Topic Models
This paper demonstrates how to use the R package stm for structural topic modeling, which allows researchers to flexibly estimate a topic model that includes document-level metadata.
mediation: R Package for Causal Mediation Analysis
The mediation package implements a comprehensive suite of statistical tools for conducting causal mediation analysis in applied empirical research and implements a statistical method for dealing with multiple (causally dependent) mediators, which are often encountered in practice.
“Who are these people?” Evaluating the demographic characteristics and political preferences of MTurk survey respondents
As Amazon’s Mechanical Turk (MTurk) has surged in popularity throughout political science, scholars have increasingly challenged the external validity of inferences made drawing upon MTurk samples.
Causal Mediation Analysis
Estimating the mechanisms that connect explanatory variables with the explained variable, also known as “mediation analysis,” is central to a variety of social-science fields, especially psychology,
Experimental designs for identifying causal mechanisms
This work considers several experimental designs that help to identify average natural indirect effects and uses recent social science experiments to illustrate the key ideas that underlie each of the designs proposed.
Computer-Assisted Text Analysis for Comparative Politics
Practical issues that arise in the processing, management, translation, and analysis of textual data are discussed with a particular focus on how procedures differ across languages.