David B. Wolfson

1.9k total citations
54 papers, 1.4k citations indexed

About

David B. Wolfson is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, David B. Wolfson has authored 54 papers receiving a total of 1.4k indexed citations (citations by other indexed papers that have themselves been cited), including 33 papers in Statistics and Probability, 13 papers in Artificial Intelligence and 8 papers in Statistics, Probability and Uncertainty. Recurrent topics in David B. Wolfson's work include Statistical Methods and Inference (17 papers), Statistical Methods and Bayesian Inference (15 papers) and Bayesian Methods and Mixture Models (13 papers). David B. Wolfson is often cited by papers focused on Statistical Methods and Inference (17 papers), Statistical Methods and Bayesian Inference (15 papers) and Bayesian Methods and Mixture Models (13 papers). David B. Wolfson collaborates with scholars based in Canada, United States and France. David B. Wolfson's co-authors include Masoud Asgharian, Lawrence Joseph, Cyr Emile M’lan, Christina Wolfson, Truls Østbye, Kenneth Rockwood, David B. Hogan, Roxane du Berger, Vittorio Addona and Patrick Bélisle and has published in prestigious journals such as New England Journal of Medicine, Journal of the American Statistical Association and PLoS ONE.

In The Last Decade

David B. Wolfson

51 papers receiving 1.3k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
David B. Wolfson Canada 17 732 203 174 170 117 54 1.4k
Didier Renard Belgium 21 633 0.9× 162 0.8× 336 1.9× 42 0.2× 168 1.4× 42 1.7k
Jaap Brand Netherlands 8 347 0.5× 60 0.3× 120 0.7× 129 0.8× 161 1.4× 11 1.4k
Ilya Lipkovich United States 25 835 1.1× 387 1.9× 360 2.1× 80 0.5× 136 1.2× 90 1.8k
Sam Wieand United States 15 655 0.9× 170 0.8× 218 1.3× 106 0.6× 83 0.7× 24 2.2k
Masoud Asgharian Canada 10 459 0.6× 201 1.0× 102 0.6× 128 0.8× 111 0.9× 29 952
Karl E. Peace United States 20 398 0.5× 68 0.3× 150 0.9× 121 0.7× 100 0.9× 85 1.2k
Vanessa Didelez Germany 23 817 1.1× 47 0.2× 224 1.3× 214 1.3× 158 1.4× 77 2.3k
Daowen Zhang United States 23 737 1.0× 38 0.2× 116 0.7× 239 1.4× 60 0.5× 50 1.9k
Byron Wm. Brown United States 20 404 0.6× 68 0.3× 206 1.2× 38 0.2× 122 1.0× 29 1.6k
Jacobo de Uña‐Álvarez Spain 20 876 1.2× 17 0.1× 121 0.7× 287 1.7× 38 0.3× 94 1.6k

Countries citing papers authored by David B. Wolfson

Since Specialization
Citations

This map shows the geographic impact of David B. Wolfson'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 David B. Wolfson with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites David B. Wolfson more than expected).

Fields of papers citing papers by David B. Wolfson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by David B. Wolfson. 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 David B. Wolfson. The network helps show where David B. Wolfson may publish in the future.

Co-authorship network of co-authors of David B. Wolfson

This figure shows the co-authorship network connecting the top 25 collaborators of David B. Wolfson. A scholar is included among the top collaborators of David B. Wolfson based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with David B. Wolfson. David B. Wolfson is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Wolfson, David B., et al.. (2022). Stacked survival models for residual lifetime data. BMC Medical Research Methodology. 22(1). 10–10. 1 indexed citations
2.
Wolfson, David B., et al.. (2020). Parametric models for combined failure time data from an incident cohort study and a prevalent cohort study with follow-up. The International Journal of Biostatistics. 17(2). 283–293. 4 indexed citations
3.
Sun, Weimin, Ke Zhang, Yan Liu, et al.. (2020). Development and Validation of a 34‐Gene Inherited Cancer Predisposition Panel Using Next‐Generation Sequencing. BioMed Research International. 2020(1). 3289023–3289023. 5 indexed citations
4.
Wolfson, David B., et al.. (2019). Parametric modelling of prevalent cohort data with uncertainty in the measurement of the initial onset date. Lifetime Data Analysis. 26(2). 389–401. 3 indexed citations
5.
Karunananthan, Sathya, Erica E. M. Moodie, Howard Bergman, et al.. (2019). The association between physical function and proximity to death in older adults: a multilevel analysis of 4,150 decedents from the Cardiovascular Health Study. Annals of Epidemiology. 35. 59–65.e5. 2 indexed citations
6.
Strom, Charles M., Ben Anderson, David Tsao, et al.. (2017). Improving the Positive Predictive Value of Non-Invasive Prenatal Screening (NIPS). PLoS ONE. 12(3). e0167130–e0167130. 11 indexed citations
7.
Khalili, Abbas, et al.. (2016). Simultaneous variable selection and de-coarsening in multi-path change-point models. Journal of Multivariate Analysis. 147. 202–217. 1 indexed citations
8.
Sanders, Heather, Hairong Li, Lin Ma, et al.. (2016). Mutation Yield of a 34-Gene Solid Tumor Panel in Community-Based Tumor Samples. Molecular Diagnosis & Therapy. 20(3). 241–253. 1 indexed citations
9.
Magalhaes, Sandra, Maura Pugliatti, Ilaria Casetta, et al.. (2015). The EnvIMS Study: Design and Methodology of an International Case-Control Study of Environmental Risk Factors in Multiple Sclerosis. Neuroepidemiology. 44(3). 173–181. 16 indexed citations
10.
Addona, Vittorio, et al.. (2012). Testing the assumptions for the analysis of survival data arising from a prevalent cohort study with follow-up. The International Journal of Biostatistics. 8(1). 22–22. 7 indexed citations
11.
Beckage, Brian, Lawrence Joseph, Patrick Bélisle, David B. Wolfson, & William Platt. (2007). Bayesian change‐point analyses in ecology. New Phytologist. 174(2). 456–467. 47 indexed citations
12.
Addona, Vittorio & David B. Wolfson. (2006). A formal test for the stationarity of the incidence rate using data from a prevalent cohort study with follow-up. Lifetime Data Analysis. 12(3). 267–284. 63 indexed citations
13.
Asgharian, Masoud, David B. Wolfson, & Xun Zhang. (2005). Checking stationarity of the incidence rate using prevalent cohort survival data. Statistics in Medicine. 25(10). 1751–1767. 51 indexed citations
14.
Wolfson, Christina, David B. Wolfson, Masoud Asgharian, et al.. (2001). A Reevaluation of the Duration of Survival after the Onset of Dementia. New England Journal of Medicine. 344(15). 1111–1116. 405 indexed citations
15.
Joseph, L., David B. Wolfson, Patrick Bélisle, et al.. (1999). Taking Account of Between-Patient Variability When Modeling Decline in Alzheimer's Disease. American Journal of Epidemiology. 149(10). 963–973. 17 indexed citations
16.
Wolfson, Christina & David B. Wolfson. (1995). Studies of the latency period in multiple sclerosis. Acta Neurologica Scandinavica. 91(S161). 89–92. 7 indexed citations
17.
Wolfson, Christina, et al.. (1993). Multiple Sclerosis: A Comparison of the Latent Periods of Different Populations. Neuroepidemiology. 12(5). 300–306. 4 indexed citations
18.
Joseph, Lawrence & David B. Wolfson. (1992). Estimation in multi-path change-point problems. Communication in Statistics- Theory and Methods. 21(4). 897–913. 33 indexed citations
19.
McDunnough, Philip & David B. Wolfson. (1980). FIXED VERSUS RANDOM SAMPLING OF CERTAIN CONTINUOUS PARAMETER PROCESSES. Australian Journal of Statistics. 22(1). 40–49. 6 indexed citations
20.
Wolfson, David B.. (1976). A Lindeberg-type theorem. Stochastic Processes and their Applications. 4(2). 203–213.

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.

Explore authors with similar magnitude of impact

Breakdown of academic impact, for papers by Didier Renard Breakdown of academic impact, for papers by Jaap Brand Breakdown of academic impact, for papers by Ilya Lipkovich Breakdown of academic impact, for papers by Sam Wieand Breakdown of academic impact, for papers by Masoud Asgharian Breakdown of academic impact, for papers by Karl E. Peace Breakdown of academic impact, for papers by Vanessa Didelez Breakdown of academic impact, for papers by Daowen Zhang Breakdown of academic impact, for papers by Byron Wm. Brown Breakdown of academic impact, for papers by Jacobo de Uña‐Álvarez
Rankless by CCL
2026