Open AccessDissertation
Bayesian Methods in High-Dimensional Sparse Mediation Analysis
Yanyi Song
- 01 Jan 2020
About: The article was published on 01 Jan 2020. and is currently open access. The article focuses on the topics: Environmental exposure & Bayesian probability.
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References
The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations.
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TL;DR: A new method for estimation in linear models called the lasso, which minimizes the residual sum of squares subject to the sum of the absolute value of the coefficients being less than a constant, is proposed.
•Book
Belief, Attitude, Intention and Behavior: An Introduction to Theory and Research
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- 01 Jun 1975
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•Book
Statistical Analysis with Missing Data
Roderick J. A. Little,Donald B. Rubin +1 more
- 01 Jan 1987
TL;DR: This work states that maximum Likelihood for General Patterns of Missing Data: Introduction and Theory with Ignorable Nonresponse and large-Sample Inference Based on Maximum Likelihood Estimates is likely to be high.
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