Bayesian (non)linear random effects mediation models: Evaluating the impact of omitting confounders.

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Publication Details

Journal
Psychological Methods
Published
2024-12-30
DOI
https://doi.org/10.1037/met0000721
Citations
1
Primary Topic
Bayesian Modeling and Causal Inference
Type
article
Field-Weighted Citation Impact
0.35
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article

Bayesian (non)linear random effects mediation models: Evaluating the impact of omitting confounders.

Nidhi Kohli, Eric F. Lock, Ziwei Zhang
1 citations
Psychological Methods
Bayesian Modeling and Causal Inference
0.35
article

Bayesian (non)linear random effects mediation models: Evaluating the impact of omitting confounders.

Nidhi Kohli, Eric F. Lock, Ziwei Zhang
article en
1 citations

Abstract

No abstract available for this paper.
Psychological Methods
University of Minnesota (US), Minnesota Department of Education (US)
Reduced inequalities
Openalex Percentile: Top 30%
Bayesian Modeling and Causal Inference
0.35
DOISourceOpenAlex
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Bayesian (non)linear random effects mediation models: Evaluating the impact of omitting confounders. — Nidhi Kohli, Eric F. Lock, et al. · Psychological Methods (2024) | TGRS Research Map | TGRS