Michael Escobar

9.2k citations
97 papers · 6.4k · 2 hit papers · h-index 36

Impact in

Papers in

Michael Escobar

91 papers receiving 6.0k citations

Michael Escobar's Hit Papers

Bayesian Density Estimation and Inference Using Mixtures 1995 · 1.4k citations
1.4k0+11+22Years since publication4008001.2k

Peers

Michael Escobar
Comparison fields: 5 of 193
  • Statistics and Probability 1.6k
  • Developmental and Educational Psychology 1.4k
  • Artificial Intelligence 1.9k
  • Clinical Psychology 659
  • Cognitive Neuroscience 551
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Citations per year

Countries citing papers authored by Michael Escobar

Since Specialization
Citations

This map shows the geographic impact of Michael Escobar's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Michael Escobar with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Michael Escobar more than expected).

Fields of papers citing papers by Michael Escobar

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael Escobar. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Michael Escobar. The network helps show where Michael Escobar may publish in the future.

Co-authors

The 25 scholars most cited alongside Michael Escobar, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Michael Escobar Line = papers co-authored together Michael Escobar links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown

Showing the 20 most-cited of 97 papers — load more, or switch the sort, to bring in the rest.

#Work
1
Bayesian Density Estimation and Inference Using Mixtures
Hit paper breakdown →
19951450
2
Evidence That Dyslexia May Represent the Lower Tail of a Normal Distribution of Reading Ability
Hit paper breakdown →
1992540
3 2001373
4 1994362
5 1999284
6 2002271
7 1995248
8 2000210
9
Prevalence of reading disability in boys and girls. Results of the Connecticut Longitudinal Study.
1990194
10 2004170
11 2004155
12 2002107
13
Incidence and estimated rates of residual risk for HIV, hepatitis C, hepatitis B and human T-cell lymphotropic viruses in blood donors in Canada, 1990-2000.
2003101
14 199497
15 200296
16 199492
17 201581
18 200777
19 199472
20 200871

About Michael Escobar

Michael Escobar is a scholar working on Epidemiology, Statistics and Probability, Artificial Intelligence, Clinical Psychology and Emergency Medicine, having authored 97 papers that have together received 6.4k indexed citations. Recurring topics across this work include Traumatic Brain Injury Research (16 papers), Statistical Methods and Inference (10 papers), Bayesian Methods and Mixture Models (9 papers), Statistical Methods and Bayesian Inference (9 papers), Trauma and Emergency Care Studies (6 papers), Traumatic Brain Injury and Neurovascular Disturbances (5 papers), Language Development and Disorders (5 papers) and Child and Adolescent Psychosocial and Emotional Development (5 papers). The work is most often cited by research in Statistics and Probability (1.6k citations), Developmental and Educational Psychology (1.4k citations), Artificial Intelligence (1.9k citations), Clinical Psychology (659 citations) and Cognitive Neuroscience (551 citations). Michael Escobar has collaborated with scholars based in Canada, United States and Ireland. Frequent co-authors include Mike West, Joseph H. Beitchman, Leslie Atkinson, Jack Μ. Fletcher, Sally E. Shaywitz, Bennett A. Shaywitz, Beth Wilson, Arlene Young, Lori Douglas and Robert Makuch. Their work appears in journals such as PLoS ONE, Archives of Physical Medicine and Rehabilitation, Journal of the American Statistical Association, Scientific Reports and Statistics in Medicine.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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