M. Masson

Cognitive Neuroscience · 1983–2016

A researcher in the Science corpus: 7 papers; trusts 20 researchers and is trusted by 95 researchers here, as inferred from the citation graph.

Subfields

• Cognitive Neuroscience — 16 citations into it; #1,143 of 10,852 by trust here, #5,291 by citations
• Statistics and Probability — 16 citations into it
• Developmental and Educational Psychology — 13 citations into it; #73 of 8,223 by trust here, #1,270 by citations
• Experimental and Cognitive Psychology — 11 citations into it
• Artificial Intelligence — 8 citations into it

Whom M. Masson trusts overall

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

1. Eric-Jan Wagenmakers
2. Hirotugu Akaike
3. P. Lachenbruch
4. Robert E. Kass
5. Jeffrey N. Rouder
6. Adrian E. Raftery
7. John K. Kruschke
8. James O. Berger
9. Paul L. Speckman
10. Deepayan Sarkar

Who trusts M. Masson overall

1. Ethan Gotlieb Wilcox
2. Jamie I. D. Campbell
3. Richard Futrell
4. Julie A. Van Dyke
5. J. D. de Groot
6. Farouk S. Nathoo
7. L. Steg
8. Valerie A. Thompson
9. Andrea E. Martin
10. Florencia Reali

Papers from M. Masson's perspective

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

1. Bayes factors
2. A new look at the statistical model identification
3. Bayesian estimation supersedes the t test. (Journal of experimental psychology. General)
4. Using confidence intervals for graphically based data interpretation. (Canadian journal of experimental psychology = Revue canadienne de psychologie experimentale)
5. The Intrinsic Bayes Factor for Model Selection and Prediction
6. Data Analysis Using Regression and Multilevel/Hierarchical Models
7. A tutorial on a practical Bayesian alternative to null-hypothesis significance testing (Behavior Research Methods)
8. Statistical Power Analysis for the Behavioral Sciences (2nd ed.)
9. Estimating the Dimension of a Model
10. Default Bayes factors for ANOVA designs

Their papers

• Bayesian alternatives to null-hypothesis significance testing for repeated-measures designs (2016) — 56 citations
• So Much to Read, So Little Time (2016) — 296 citations
• A tutorial on a practical Bayesian alternative to null-hypothesis significance testing (2011) — 773 citations
• A linear mixed model analysis of masked repetition priming (2010) — 249 citations
• Using confidence intervals for graphically based data interpretation. (2003) — 805 citations
• Prime Validity Affects Masked Repetition Priming: Evidence for an Episodic Resource Account of Priming (2001) — 142 citations
• Conceptual processing of text during skimming and rapid sequential reading (1983)