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Pósch, Krisztián – Sociological Methods & Research, 2021
Complex social scientific theories are conventionally tested using linear structural equation modeling (SEM). However, the underlying assumptions of linear SEM often prove unrealistic, making the decomposition of direct and indirect effects problematic. Recent advancements in causal mediation analysis can help to address these shortcomings,…
Descriptors: Social Theories, Causal Models, Structural Equation Models, Statistical Analysis
Hertog, Steffen – Sociological Methods & Research, 2023
In mixed methods approaches, statistical models are used to identify "nested" cases for intensive, small-n investigation for a range of purposes, including notably the examination of causal mechanisms. This article shows that under a commonsense interpretation of causal effects, large-n models allow no reliable conclusions about effect…
Descriptors: Case Studies, Generalization, Prediction, Mixed Methods Research
Wodtke, Geoffrey T. – Sociological Methods & Research, 2020
Social scientists are often interested in estimating the marginal effects of a time-varying treatment on an end-of-study continuous outcome. With observational data, estimating these effects is complicated by the presence of time-varying confounders affected by prior treatments, which may lead to bias in conventional regression and matching…
Descriptors: Regression (Statistics), Computation, Statistical Analysis, Statistical Bias
An, Weihua; Winship, Christopher – Sociological Methods & Research, 2017
In this article, we review popular parametric models for analyzing panel data and introduce the latest advances in matching methods for panel data analysis. To the extent that the parametric models and the matching methods offer distinct advantages for drawing causal inference, we suggest using both to cross-validate the evidence. We demonstrate…
Descriptors: Causal Models, Statistical Inference, Interviews, Race
An, Weihua – Sociological Methods & Research, 2016
One interesting idea in social network analysis is the directionality test that utilizes the directions of social ties to help identify peer effects. The null hypothesis of the test is that if contextual factors are the only force that affects peer outcomes, the estimated peer effects should not differ, if the directions of social ties are…
Descriptors: Peer Relationship, Social Networks, Statistical Analysis, Network Analysis
Katz, Jack – Sociological Methods & Research, 2015
There is unexamined potential for developing and testing rival causal explanations in the type of data that participant observation is best suited to create: descriptions of in situ social interaction crafted from the participants' perspectives. By intensively examining a single ethnography, we can see how multiple predictions can be derived from…
Descriptors: Abstract Reasoning, Observation, Field Studies, Notetaking