Malcolm Farrow

814 total citations
43 papers, 523 citations indexed

About

Malcolm Farrow is a scholar working on Statistics and Probability, Artificial Intelligence and Information Systems. According to data from OpenAlex, Malcolm Farrow has authored 43 papers receiving a total of 523 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 8 papers in Artificial Intelligence and 6 papers in Information Systems. Recurrent topics in Malcolm Farrow's work include Software Engineering Research (6 papers), Software Reliability and Analysis Research (6 papers) and Statistical Methods and Bayesian Inference (4 papers). Malcolm Farrow is often cited by papers focused on Software Engineering Research (6 papers), Software Reliability and Analysis Research (6 papers) and Statistical Methods and Bayesian Inference (4 papers). Malcolm Farrow collaborates with scholars based in United Kingdom, Germany and Iraq. Malcolm Farrow's co-authors include Wallace Arthur, Michael Oakes, Warren Gilchrist, Michael Goldstein, Brian K. Saxby, Kevin J. Wilson, Dilum Dissanayake, Margaret Bell, Allan Carmichael and Graham Burns and has published in prestigious journals such as Blood, Technometrics and Journal of Animal Ecology.

In The Last Decade

Malcolm Farrow

42 papers receiving 488 citations

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Malcolm Farrow United Kingdom	13	70	51	43	43	43	43	523
Lamiae Azizi Australia	11	58 0.8×	37 0.7×	35 0.8×	8 0.2×	18 0.4×	20	454
Bruno Scarpa Italy	19	73 1.0×	31 0.6×	114 2.7×	8 0.2×	35 0.8×	88	1.1k
Julia Schiffner Germany	12	64 0.9×	64 1.3×	14 0.3×	5 0.1×	28 0.7×	20	497
Bernd Streitberg Germany	9	61 0.9×	36 0.7×	84 2.0×	2 0.0×	34 0.8×	15	660
Giuseppe Casalicchio Germany	9	180 2.6×	100 2.0×	34 0.8×	3 0.1×	21 0.5×	20	635
Sarah Friedrich Germany	17	29 0.4×	49 1.0×	105 2.4×	6 0.1×	28 0.7×	41	730
Karel Kupka Czechia	15	30 0.4×	41 0.8×	13 0.3×	10 0.2×	11 0.3×	37	527
San Francisco United States	9	109 1.6×	46 0.9×	7 0.2×	2 0.0×	34 0.8×	47	478
Rachel MacKay Altman Canada	9	115 1.6×	81 1.6×	101 2.3×	6 0.1×	33 0.8×	21	452

Countries citing papers authored by Malcolm Farrow

Since Specialization

Citations

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

Fields of papers citing papers by Malcolm Farrow

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Malcolm Farrow

This figure shows the co-authorship network connecting the top 25 collaborators of Malcolm Farrow. A scholar is included among the top collaborators of Malcolm Farrow 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 Malcolm Farrow. Malcolm Farrow is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

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20 of 20 papers shown

Farrow, Malcolm, Graham Ball, Sara Graziadio, et al.. (2024). Artificial neural network risk prediction of COPD exacerbations using urine biomarkers. ERJ Open Research. 11(3). 797–2024. 2 indexed citations

Farrow, Malcolm & Kevin J. Wilson. (2020). Identifying the effect of public holidays on daily demand for gas. Durham Research Online (Durham University). 1 indexed citations

Dissanayake, Dilum, et al.. (2018). Investigating car users' attitudes to climate change using multiple correspondence analysis. Journal of Transport Geography. 72. 237–247. 33 indexed citations

Wilson, Kevin J. & Malcolm Farrow. (2016). Bayes linear kinematics in a dynamic survival model. International Journal of Approximate Reasoning. 80. 239–256. 1 indexed citations

Heaps, Sarah E., Richard J. Boys, & Malcolm Farrow. (2015). Bayesian Modelling of Rainfall Data by Using Non-Homogeneous Hidden Markov Models and Latent Gaussian Variables. Journal of the Royal Statistical Society Series C (Applied Statistics). 64(3). 543–568. 9 indexed citations

Keaney, N. P., et al.. (2012). Muscle weakness, health status and frequency of exacerbations in chronic obstructive pulmonary disease. Postgraduate Medical Journal. 88(1041). 372–376. 22 indexed citations

Farrow, Malcolm & Michael Goldstein. (2010). Sensitivity of decisions with imprecise utility trade-off parameters using boundary linear utility. International Journal of Approximate Reasoning. 51(9). 1100–1113. 1 indexed citations

Burns, Graham, et al.. (2007). Predictors of quality of life in chronic obstructive pulmonary disease patients with different frequency of exacerbations. Pakistan Journal of Medical Sciences. 6 indexed citations

Wolski, Witold, Malcolm Farrow, Anne‐Katrin Emde, et al.. (2006). Analytical model of peptide mass cluster centres with applications.. Proteome Science. 4(1). 18–18. 22 indexed citations

10.

Whiteley, Paul, R. H. Waring, Susan Smith, et al.. (2006). Spot urinary creatinine excretion in pervasive developmental disorders. Pediatrics International. 48(3). 292–297. 25 indexed citations

11.

Farrow, Malcolm, et al.. (2006). A productivity benchmarking case study using Bayesian credible intervals. Software Quality Journal. 14(1). 37–52. 11 indexed citations

12.

Mandal, Kaveri, Anthony J. Hildreth, Malcolm Farrow, & David W. Allen. (2004). Investigation into postoperative endophthalmitis and lessons learned. Journal of Cataract & Refractive Surgery. 30(9). 1960–1965. 9 indexed citations

13.

Farrow, Malcolm & Michael Goldstein. (2004). Trade-off sensitive experimental design: a multicriterion, decision theoretic, Bayes linear approach. Journal of Statistical Planning and Inference. 136(2). 498–526. 7 indexed citations

14.

Blackburn, James, Malcolm Farrow, & Wallace Arthur. (2002). Factors influencing the distribution, abundance and diversity of geophilomorph and lithobiomorph centipedes. Journal of Zoology. 256(2). 221–232. 12 indexed citations

15.

Saxby, Brian K., et al.. (2001). Psychological factors associated with short‐term recovery from total knee replacement. British Journal of Health Psychology. 6(1). 41–52. 46 indexed citations

16.

Farrow, Malcolm, M. J. Crowder, & David J. Hand. (1992). Analysis of Repeated Measures.. Journal of the Royal Statistical Society Series C (Applied Statistics). 41(1). 216–216. 5 indexed citations

17.

Farrow, Malcolm, et al.. (1992). C-Peptide Response to Oral Glucose and its Clinical Role in Elderly People. Age and Ageing. 21(2). 103–108. 6 indexed citations

18.

Carmichael, A.J., et al.. (1988). Magnesium free dialysis for uraemic pruritus.. BMJ. 297(6663). 1584–1585. 19 indexed citations

19.

Carmichael, Allan, et al.. (1988). Serological markers of renal itch in patients receiving long term haemodialysis. BMJ. 296(6636). 1575–1575. 33 indexed citations

20.

Arthur, Wallace & Malcolm Farrow. (1987). On detecting interactions between species in population dynamics. Biological Journal of the Linnean Society. 32(3). 271–279. 5 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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