Alexander Robitzsch

Statistics and Probability · 2008–2020

A researcher in the Science corpus: 9 papers; trusts 60 researchers and is trusted by 15 researchers here, as inferred from the citation graph.

Subfields

• Statistics and Probability — 95 citations into it; #10,977 of 12,932 by trust here, #10,855 by citations
• Management Science and Operations Research — 45 citations into it; #2,885 of 11,946 by trust here, #727 by citations
• Education — 36 citations into it; #5,058 of 11,309 by trust here, #2,462 by citations
• Experimental and Cognitive Psychology — 27 citations into it; #3,291 of 9,731 by trust here, #2,457 by citations
• Artificial Intelligence — 25 citations into it
• Computer Networks and Communications — 23 citations into it
• Social Psychology — 21 citations into it
• Economics and Econometrics — 11 citations into it

Whom Alexander Robitzsch trusts overall

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

1. Albert Maydeu-Olivares
2. Yves Rosseel
3. R. Chalmers
4. S. Green
5. Donald B. Rubin
6. Yanyun Yang
7. Peter D. Hoff
8. Joseph L. Schafer
9. B. Muthén
10. James R. Carpenter

Who trusts Alexander Robitzsch overall

1. Herbert W. Marsh
2. Alexandre J. S. Morin
3. O. Lüdtke
4. Shaljan Areepattamannil
5. Kristopher J Preacher
6. T. Asparouhov
7. Ulrich Trautwein
8. Swantje Dettmers
9. Francis L. Huang
10. Ronny Scherer

Papers from Alexander Robitzsch's perspective

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

1. INFERENCE AND MISSING DATA
2. Analysis of Incomplete Multivariate Data (Technometrics)
3. Statistical Analysis with Missing Data: Little/Statistical Analysis with Missing Data
4. Multilevel Statistical Models
5. Inference from Iterative Simulation Using Multiple Sequences
6. Multilevel analysis : an introduction to basic and advanced multilevel modeling
7. Missing data: our view of the state of the art. (Psychological methods)
8. BEYOND SEM: GENERAL LATENT VARIABLE MODELING
9. Principles and Practice of Structural Equation Modeling (2nd ed.)
10. Statistical Analysis With Missing Data

Their papers

• The multilevel latent covariate model: a new, more reliable approach to group-level effects in contextual studies. (2008) — 783 citations
• Exploratory Structural Equation Modeling, Integrating CFA and EFA: Application to Students' Evaluations of University Teaching (2009) — 1,079 citations
• Multiple Imputation of Missing Data for Multilevel Models (2018) — 164 citations
• Why Ordinal Variables Can (Almost) Always Be Treated as Continuous Variables: Clarifying Assumptions of Robust Continuous and Ordinal Factor Analysis Estimation Methods (2020) — 335 citations
• A Bayesian Approach for Estimating Multilevel Latent Contextual Models (2016) — 57 citations
• Pooling ANOVA Results From Multiply Imputed Datasets (2016) — 46 citations
• Difficulties in solving context-based PISA mathematics tasks: An analysis of students’ errors (2014) — 256 citations
• Special education students’ use of indirect addition in solving subtraction problems up to 100—A proof of the didactical potential of an ignored procedure (2012) — 53 citations
• Assessing the impact of learning environments: How to use student ratings of classroom or school characteristics in multilevel modeling (2009) — 496 citations