Peter M. Steiner
YOU?
Author Swipe
View article: Drawing Credible Directed Acyclic Graphs for Causal Inference
Drawing Credible Directed Acyclic Graphs for Causal Inference Open
Causal inference with observational studies is challenging because the identification and estimation of a causal effect rests on the untestable unconfoundedness assumption. The assumption requires researchers to determine a set of observed…
View article: Drawing Credible Directed Acyclic Graphs for Causal Inference
Drawing Credible Directed Acyclic Graphs for Causal Inference Open
Causal inference with observational studies is challenging because the identification and estimation of a causal effect rests on the untestable unconfoundedness assumption. The assumption requires researchers to determine a set of observed…
View article: Drawing Credible Directed Acyclic Graphs for Causal Inference
Drawing Credible Directed Acyclic Graphs for Causal Inference Open
Causal inference with observational studies is challenging because the identification and estimation of a causal effect rests on the untestable unconfoundedness assumption. The assumption requires researchers to determine a set of observed…
View article: Causal Mediation: Assessing Meaningful Path-specific Effects Rather than Decomposing the Total Effect
Causal Mediation: Assessing Meaningful Path-specific Effects Rather than Decomposing the Total Effect Open
Nonparametric causal mediation methods (Pearl, 2001; Robins and Greenland,1992) are commonly described as decomposing the total effect into thenatural direct and indirect effects. Here, we argue that mediation should not beunderstood in te…
View article: A new four-arm within-study comparison: Design, implementation, and data
A new four-arm within-study comparison: Design, implementation, and data Open
Within-study comparisons (WSCs) use real, rather than simulated, data to compare estimates from observational studies against benchmarks from randomized controlled trials (RCTs). A primary goal of WSCs is to assess whether well-designed qu…
View article: Drawing Directed Acyclic Graphs for Causal Inference
Drawing Directed Acyclic Graphs for Causal Inference Open
Causal inference with observational studies is challenging because the identification and estimation of a causal effect rests on the untestable unconfoundedness assumption. The assumption requires researchers to determine a set of observed…
View article: A new four-arm within-study comparison: Design, implementation, and data
A new four-arm within-study comparison: Design, implementation, and data Open
Within-study comparisons (WSCs) use real, rather than simulated, data to compare estimates from observational studies against a benchmark randomized controlled trial (RCT). A primary goal of WSCs is to assess whether well-designed quasi-ex…
View article: A new four-arm within-study comparison: Design, implementation, and data
A new four-arm within-study comparison: Design, implementation, and data Open
Within-study comparisons (WSCs) use real, rather than simulated, data to compare estimates from observational studies against a benchmark randomized controlled trial (RCT). A primary goal of WSCs is to assess whether well-designed quasi-ex…
View article: Frameworks for causal inference in psychological science
Frameworks for causal inference in psychological science Open
This chapter reviews some of the more recent developments of frameworks for causal inference, using Campbell’s familiar work on validity types and threats as a touchstone from which to examine two alternative frameworks: the potential outc…
View article: Robust Covariate Selection for Doubly Robust Estimators in Causal Inference
Robust Covariate Selection for Doubly Robust Estimators in Causal Inference Open
Doubly robust (DR) estimators are widely used in causal inference because they are consistent whenever either the outcome or propensity score (PS) model is correctly specified with regard to a covariate set that meets the adjustment criter…
View article: Correspondence measures for assessing replication success.
Correspondence measures for assessing replication success. Open
Given recent evidence challenging the replicability of results in the social and behavioral sciences, critical questions have been raised about appropriate measures for determining replication success in comparing effect estimates across s…
View article: Regression Discontinuity Designs with an Ordinal Running Variable: Evaluating the Effects of Extended Time Accommodations for English Language Learners
Regression Discontinuity Designs with an Ordinal Running Variable: Evaluating the Effects of Extended Time Accommodations for English Language Learners Open
Regression discontinuity designs are commonly used for program evaluation with continuous treatment assignment variables. But in practice, treatment assignment is frequently based on ordinal variables. In this study, we propose a regressio…
View article: A Large Deviation Approach to the Measurement of Mobility
A Large Deviation Approach to the Measurement of Mobility Open
We propose an approach to measure the mobility immanent in regular Markov processes. For this purpose, we distinguish between mobility in equilibrium and mobility associated with convergence towards equilibrium. The former aspect is measur…
View article: Ways Out of the Replication Crisis
Ways Out of the Replication Crisis Open
The talk addresses different aspects of the replication crisis in the social sciences and suggests directions to overcome the crisis. Even if direct or exact replications of research findings are hard to achieve in practice, we should aim …
View article: Moving from What Works to What Replicates: A New Framework for Evidence Based Policy Analysis
Moving from What Works to What Replicates: A New Framework for Evidence Based Policy Analysis Open
Background: Efforts to promote evidence-based practices in medicine and the social sciences (e.g., What Works Clearinghouse) assume that scientific findings are of sufficient validity to warrant their use in decision making. Replication ha…
View article: Assessing the Correspondence of Results in Replication Studies
Assessing the Correspondence of Results in Replication Studies Open
Background: Reproducibility is a hallmark of science. Instead of relying on causal conclusions from a single experimental or non-experimental study, scientific knowledge is best achieved through careful replication of studies, or meta-anal…
View article: Improving the Science in Replication Sciences
Improving the Science in Replication Sciences Open
Given the central role of replication in the accumulation of scientific knowledge, researchers have reevaluated the robustness of seemingly well established findings across multiple disciplines. Results from these efforts have not been pro…
View article: Designing Valid and Reliable Vignette Experiments for Survey Research: A Case Study on the Fair Gender Income Gap
Designing Valid and Reliable Vignette Experiments for Survey Research: A Case Study on the Fair Gender Income Gap Open
In survey research, vignette experiments typically employ short, systematically varied descriptions of situations or persons (called vignettes) to elicit the beliefs, attitudes, or behaviors of respondents with respect to the presented sce…
View article: Russian Formalism
Russian Formalism Open
Russian Formalism malist literary theory by portraying it as unoriginal and deriva tive, since in Russian letters the concern with literary form had preceded the birth of this group by decades.According to A. Maskin, "as early as 1884, eve…
View article: The Mechanics of Omitted Variable Bias: Bias Amplification and Cancellation of Offsetting Biases
The Mechanics of Omitted Variable Bias: Bias Amplification and Cancellation of Offsetting Biases Open
Causal inference with observational data frequently requires researchers to estimate treatment effects conditional on a set of observed covariates, hoping that they remove or at least reduce the confounding bias. Using a simple linear (reg…
View article: Practice of causal inference with the propensity of being zero or one: assessing the effect of arbitrary cutoffs of propensity scores
Practice of causal inference with the propensity of being zero or one: assessing the effect of arbitrary cutoffs of propensity scores Open
Causal inference methodologies have been developed for the past decade to estimate the unconfounded effect of an exposure under several key assumptions. These assumptions include, but are not limited to, the stable unit treatment value ass…