S. Depaoli

Statistics and Probability · 2014–2017

A researcher in the Science corpus: 4 papers; trusts 44 researchers and is trusted by 10 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 47 citations into it; #4,094 of 12,932 by trust here, #6,853 by citations
• Artificial Intelligence — 19 citations into it; #18,550 of 35,345 by trust here, #28,481 by citations
• Management Science and Operations Research — 18 citations into it; #4,530 of 11,946 by trust here, #9,931 by citations
• Economics and Econometrics — 8 citations into it
• Computer Networks and Communications — 7 citations into it
• Probabilistic & Bayesian Methods — 7 citations into it
• Experimental and Cognitive Psychology — 5 citations into it
• Social Psychology — 5 citations into it

Whom S. Depaoli trusts overall

Their strongest outbound trust, strongest first, inferred from their citations.

1. Jean-Paul Fox
2. Kenneth A. Bollen
3. Joop J. Hox
4. James O. Berger
5. Joseph Hilbe
6. Lawrence D. Brown
7. Sik-Yum Lee
8. Peter Congdon
9. Andrew Gelman
10. B. Muthén

Who trusts S. Depaoli overall

1. Daniel M. McNeish
2. Yue Xiao
3. R. van de Schoot
4. Steffen Zitzmann
5. Hongyun Liu
6. O. Lüdtke
7. Milica Miočević
8. K. Hau
9. Alexander Robitzsch

Papers from S. Depaoli's perspective

Ordered by how strongly the researchers S. Depaoli trusts endorse each paper. Same corpus, a different order for every researcher.

1. Stochastic Relaxation, Gibbs Distributions, and the Bayesian Restoration of Images
2. Sampling-Based Approaches to Calculating Marginal Densities
3. Multilevel analysis : an introduction to basic and advanced multilevel modeling
4. Bayesian data analysis.
5. The Accuracy of Multilevel Structural Equation Modeling With Pseudobalanced Groups and Small Samples
6. Prior distributions for variance parameters in hierarchical models (comment on article by Browne and Draper)
7. General methods for monitoring convergence of iterative simulations
8. Bayesian factor analysis for multilevel binary observations
9. Sufficient Sample Sizes for Multilevel Modeling
10. Bayesian latent variable models for clustered mixed outcomes

Their papers

• A Bayesian Approach to Multilevel Structural Equation Modeling With Continuous and Dichotomous Outcomes (2015) — 157 citations
• Improving Transparency and Replication in Bayesian Statistics: The WAMBS-Checklist (2017) — 383 citations
• Additional Information: The GRoLTS-checklist: Guidelines for Reporting on Latent Trajectory Studies (2016) — 591 citations
• Bayesian analyses : where to start and what to report (2014) — 179 citations