Srabashi Basu

979 total citations
21 papers, 705 citations indexed

About

Srabashi Basu is a scholar working on Statistics and Probability, Artificial Intelligence and Statistics, Probability and Uncertainty. According to data from OpenAlex, Srabashi Basu has authored 21 papers receiving a total of 705 indexed citations (citations by other indexed papers that have themselves been cited), including 11 papers in Statistics and Probability, 3 papers in Artificial Intelligence and 3 papers in Statistics, Probability and Uncertainty. Recurrent topics in Srabashi Basu's work include Statistical Methods and Bayesian Inference (7 papers), Advanced Statistical Methods and Models (6 papers) and Statistical Methods and Inference (5 papers). Srabashi Basu is often cited by papers focused on Statistical Methods and Bayesian Inference (7 papers), Advanced Statistical Methods and Models (6 papers) and Statistical Methods and Inference (5 papers). Srabashi Basu collaborates with scholars based in United States, India and Hong Kong. Srabashi Basu's co-authors include Daniel F. Heitjan, Jacqueline A. Pugh, Hisham R. Ashry, Lawrence A. Lavery, Lawrence B. Harkless, Ayanendranath Basu, J. Richard Landis, Tapan K. Mukherjee, Suvro Banerjee and Chanseok Park and has published in prestigious journals such as Diabetes Care, Diabetes and American Journal of Epidemiology.

In The Last Decade

Srabashi Basu

20 papers receiving 663 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Srabashi Basu United States 10 214 212 89 77 70 21 705
Airlane Pereira Alencar Brazil 19 47 0.2× 75 0.4× 94 1.1× 34 0.4× 24 0.3× 79 1.1k
Yousung Park South Korea 9 131 0.6× 89 0.4× 8 0.1× 67 0.9× 35 0.5× 41 772
Kelvin Bryan Tan Singapore 19 74 0.3× 8 0.0× 66 0.7× 208 2.7× 26 0.4× 78 885
Vance W. Berger United States 19 22 0.1× 734 3.5× 18 0.2× 100 1.3× 46 0.7× 76 1.4k
Girdhar G. Agarwal India 16 15 0.1× 84 0.4× 13 0.1× 58 0.8× 16 0.2× 51 834
Basílio de Bragança Pereira Brazil 14 28 0.1× 67 0.3× 16 0.2× 34 0.4× 23 0.3× 73 606
Martin Seneviratne United States 13 54 0.3× 9 0.0× 13 0.1× 42 0.5× 237 3.4× 26 690
Nira Herrmann United States 12 16 0.1× 42 0.2× 13 0.1× 45 0.6× 32 0.5× 38 665
Darren Lunn United Kingdom 9 57 0.3× 15 0.1× 4 0.0× 55 0.7× 46 0.7× 18 656
Bilal A. Mateen United Kingdom 14 70 0.3× 19 0.1× 7 0.1× 54 0.7× 137 2.0× 42 905

Countries citing papers authored by Srabashi Basu

Since Specialization
Citations

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

Fields of papers citing papers by Srabashi Basu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Srabashi Basu. 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 Srabashi Basu. The network helps show where Srabashi Basu may publish in the future.

Co-authorship network of co-authors of Srabashi Basu

This figure shows the co-authorship network connecting the top 25 collaborators of Srabashi Basu. A scholar is included among the top collaborators of Srabashi Basu 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 Srabashi Basu. Srabashi Basu 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.
Banerjee, Suvro, Tapan K. Mukherjee, & Srabashi Basu. (2016). Prevalence, awareness, and control of hypertension in the slums of Kolkata. Indian Heart Journal. 68(3). 286–294. 34 indexed citations
2.
Basu, Srabashi, Ayanendranath Basu, & M. C. Jones. (2006). Robust and Efficient Parametric Estimation for Censored Survival Data. Annals of the Institute of Statistical Mathematics. 58(2). 341–355. 9 indexed citations
3.
Rao, Arni S. R. Srinivasa, Srabashi Basu, Ayanendranath Basu, & Jayanta K. Ghosh. (2005). Parametric models for incubation distribution in presence of left and right censoring. NOT FOUND REPOSITORY (Indian Institute of Science Bangalore). 36(7). 371–384. 2 indexed citations
4.
Basu, Srabashi, et al.. (2003). Words in DNA sequences: some case studies based on their frequency statistics. Journal of Mathematical Biology. 46(6). 479–503. 9 indexed citations
5.
Basu, Ayanendranath, Surajit Ray, Chanseok Park, & Srabashi Basu. (2002). Improved power in multinomial goodness-of-fit tests. Journal of the Royal Statistical Society Series D (The Statistician). 51(3). 381–393. 5 indexed citations
6.
Basu, Srabashi. (2001). Improved Small Sample Inference Procedures for Epidemiological Parameters Under Cross-Sectional Sampling. Journal of the Royal Statistical Society Series D (The Statistician). 50(3). 309–319. 5 indexed citations
7.
Mitra, Sinjini, Srabashi Basu, & Ayanendranath Basu. (2000). Exact minimum disparity inference in complex multinomial models. METRON. 167–185.
8.
Basu, Srabashi, Ayanendranath Basu, & Aparna Raychaudhuri. (1999). Measuring Agreement Between Two Raters for Ordinal Response: a Model-based Approach. Journal of the Royal Statistical Society Series D (The Statistician). 48(3). 339–348. 8 indexed citations
9.
Basu, Ayanendranath & Srabashi Basu. (1998). PENALIZED MINIMUM DISPARITY METHODS FOR MULTINOMIAL MODELS. 25 indexed citations
10.
Basu, Srabashi, et al.. (1997). Predictors of the Rate of Renal Function Decline in Non-Insulin-Dependent Diabetes mellitus. American Journal of Nephrology. 17(1). 59–67. 26 indexed citations
11.
Basu, Srabashi, et al.. (1997). Robust tests for equality of two population means under the normal model. Communications in Statistics - Simulation and Computation. 26(1). 333–353. 1 indexed citations
12.
Mulrow, Cynthia D., et al.. (1996). Function and Medical Comorbidity in South Texas Nursing Home Residents: Variations by Ethnic Group. Journal of the American Geriatrics Society. 44(3). 279–284. 19 indexed citations
13.
Heitjan, Daniel F. & Srabashi Basu. (1996). Distinguishing “Missing at Random” and “Missing Completely at Random”. The American Statistician. 50(3). 207–213. 161 indexed citations
14.
Basu, Ayanendranath, Ian R. Harris, & Srabashi Basu. (1996). Tests of hypotheses in discrete models based on the penalized Hellinger distance. Statistics & Probability Letters. 27(4). 367–373. 12 indexed citations
15.
Heitjan, Daniel F. & Srabashi Basu. (1996). Distinguishing "Missing at Random" and "Missing Completely at Random". The American Statistician. 50(3). 207–207. 69 indexed citations
16.
Park, Chanseok, Ayanendranath Basu, & Srabashi Basu. (1995). Robust minimum distance inference based on combined distances. Communications in Statistics - Simulation and Computation. 24(3). 653–673. 8 indexed citations
17.
Basu, Srabashi & Ayanendranath Basu. (1995). Comparison of several goodness‐of‐fit tests for the kappa statistic based on exact power and coverage probability. Statistics in Medicine. 14(4). 347–356. 8 indexed citations
18.
Basu, Srabashi & J. Richard Landis. (1995). Model-based Estimation of Population Attributable Risk under Cross-sectional Sampling. American Journal of Epidemiology. 142(12). 1338–1343. 33 indexed citations
19.
Basu, Srabashi, Aparna Raychaudhuri, & Ayanendranath Basu. (1995). Improving precision through modelling: an illustration with hierarchical kappa. Communications in Statistics - Simulation and Computation. 24(2). 399–408. 1 indexed citations
20.
Pugh, Jacqueline A., et al.. (1995). NIDDM is the Major Cause of Diabetic End-Stage Renal Disease: More Evidence From a Tri-Ethnic Community. Diabetes. 44(12). 1375–1380. 66 indexed citations

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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