D Faries

462 total citations
24 papers, 371 citations indexed

About

D Faries is a scholar working on Statistics and Probability, Economics and Econometrics and Psychiatry and Mental health. According to data from OpenAlex, D Faries has authored 24 papers receiving a total of 371 indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Statistics and Probability, 8 papers in Economics and Econometrics and 5 papers in Psychiatry and Mental health. Recurrent topics in D Faries's work include Health Systems, Economic Evaluations, Quality of Life (8 papers), Statistical Methods in Clinical Trials (8 papers) and Advanced Causal Inference Techniques (7 papers). D Faries is often cited by papers focused on Health Systems, Economic Evaluations, Quality of Life (8 papers), Statistical Methods in Clinical Trials (8 papers) and Advanced Causal Inference Techniques (7 papers). D Faries collaborates with scholars based in United States, United Kingdom and Germany. D Faries's co-authors include Haya Ascher‐Svanum, Bruce J. Kinon, Allen W. Nyhuis, Robert W. Baker, Anantha Shekhar, Xiaomei Peng, David J. DeBrota, Mark A. Demitrack, John M. Herrera and William Z. Potter and has published in prestigious journals such as Journal of Clinical Oncology, SHILAP Revista de lepidopterología and Biological Psychiatry.

In The Last Decade

D Faries

23 papers receiving 351 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
D Faries United States 9 164 62 59 56 55 24 371
Barbara van Zwieten‐Boot Netherlands 9 187 1.1× 65 1.0× 86 1.5× 12 0.2× 41 0.7× 11 502
Coralee Yale United States 12 108 0.7× 30 0.5× 27 0.5× 17 0.3× 41 0.7× 27 408
Florence Marteau France 10 62 0.4× 89 1.4× 20 0.3× 6 0.1× 45 0.8× 30 356
M Kerekeş Germany 3 49 0.3× 21 0.3× 76 1.3× 31 0.6× 31 0.6× 6 337
D. Friedlander New Zealand 7 52 0.3× 36 0.6× 16 0.3× 7 0.1× 29 0.5× 13 358
Teresa Filshtein United States 12 181 1.1× 14 0.2× 27 0.5× 18 0.3× 18 0.3× 18 419
Meredith Lotz United States 6 65 0.4× 15 0.2× 20 0.3× 17 0.3× 28 0.5× 7 308
Scott C. Zimmerman United States 11 124 0.8× 28 0.5× 24 0.4× 32 0.6× 4 0.1× 39 427
Hélène Sapin United States 11 76 0.5× 23 0.4× 85 1.4× 6 0.1× 21 0.4× 34 524

Countries citing papers authored by D Faries

Since Specialization
Citations

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

Fields of papers citing papers by D Faries

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of D Faries

This figure shows the co-authorship network connecting the top 25 collaborators of D Faries. A scholar is included among the top collaborators of D Faries 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 D Faries. D Faries 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.
Zagar, Anthony J., Zbigniew Kadziola, Ilya Lipkovich, David Madigan, & D Faries. (2022). Evaluating bias control strategies in observational studies using frequentist model averaging. Journal of Biopharmaceutical Statistics. 32(2). 247–276. 11 indexed citations
2.
Cui, Zhanglin Lin, Lisa M. Hess, Robert Goodloe, & D Faries. (2018). Application and comparison of generalized propensity score matching versus pairwise propensity score matching. Journal of Comparative Effectiveness Research. 7(9). 923–934. 5 indexed citations
3.
Happich, Michael, Alan Brnabic, D Faries, et al.. (2016). Reweighting Rct Evidence To Better Reflect Real Life: A Case Study of The Innovation Medicines Initiative. Value in Health. 19(7). A711–A711. 2 indexed citations
4.
Belger, Mark, Alan Brnabic, Zbigniew Kadziola, Helmut Petto, & D Faries. (2015). Alternative Weighting Approaches For Matching Adjusted Indirect Comparisons (Maic). Value in Health. 18(3). A31–A32. 6 indexed citations
5.
Belger, Mark, Alan Brnabic, Zbigniew Kadziola, Helmut Petto, & D Faries. (2015). Inclusion Of Multiple Studies In Matching Adjusted Indirect Comparisons (Maic). Value in Health. 18(3). A33–A33. 7 indexed citations
6.
Kadziola, Zbigniew, Shu Yang, Guido W. Imbens, Zhanglin Lin Cui, & D Faries. (2014). Propensity Score Matching and Subclassification With Multi-Level Treatments. Value in Health. 17(7). A587–A587. 1 indexed citations
7.
Kennedy‐Martin, Tessa, et al.. (2014). A scoping literature review on the external validity of randomized controlled trial populations. Value in Health. 17(3). A182–A182. 1 indexed citations
8.
9.
Ascher‐Svanum, Haya, Xiaomei Peng, D Faries, Robert R. Conley, & Kory Schuh. (2011). Decline in hospitalization risk and health care cost after initiation of depot antipsychotics in the treatment of schizophrenia. SHILAP Revista de lepidopterología. 3. 9–9. 49 indexed citations
10.
Peng, Xiaomei, Haya Ascher‐Svanum, D Faries, et al.. (2011). Cost-effectiveness of early responders versus early nonresponders to atypical antipsychotic therapy. SHILAP Revista de lepidopterología. 3. 79–79. 11 indexed citations
11.
12.
Pennella, Eduardo J., Gerson Peltz, Allicia C. Girvan, et al.. (2010). Interim results of an observational study evaluating the impact of ethnic origin on the effect of second-line treatment with pemetrexed (P) for advanced non-small cell lung cancer (NSCLC).. Journal of Clinical Oncology. 28(15_suppl). e18055–e18055. 1 indexed citations
13.
Lang, Kathleen, Martin Marciniak, D Faries, et al.. (2008). Trends and predictors of first-line chemotherapy use among elderly patients with advanced non-small cell lung cancer in the United States. Lung Cancer. 63(2). 264–270. 50 indexed citations
14.
Lipkovich, Ilya, David H. Adams, Craig Mallinckrodt, et al.. (2008). Evaluating dose response from flexible dose clinical trials. BMC Psychiatry. 8(1). 3–3. 31 indexed citations
15.
Clements, Karen, et al.. (2008). The impact of tumor histology on survival among elderly chemotherapy-treated patients with stage IIIB/IV NSCLC. Journal of Clinical Oncology. 26(15_suppl). 19067–19067. 1 indexed citations
16.
Ascher‐Svanum, Haya, Allen W. Nyhuis, D Faries, et al.. (2007). Clinical, Functional, and Economic Ramifications of Early Nonresponse to Antipsychotics in the Naturalistic Treatment of Schizophrenia. Schizophrenia Bulletin. 34(6). 1163–1171. 83 indexed citations
17.
Ascher‐Svanum, Haya, et al.. (2004). PMH50 THE ROLE OF ANTIPARKINSONIAN AGENTS IN SELFREPORTED COGNITIVE IMPAIRMENT AND AKATHISIA DURING THE LONG-TERM TREATMENT OF SCHIZOPHRENIA. Value in Health. 7(3). 279–279. 1 indexed citations
18.
Faries, D, et al.. (2004). PE1 ASSESSING EFFECTIVENESS IN THE PRESENCE OF TREATMENT SWITCHING: DATA FROM AN EFFECTIVENESS STUDY OF ANTIPSYCHOTICS. Value in Health. 7(3). 231–232. 1 indexed citations
19.
Nyhuis, Allen W., Michael D. Stensland, & D Faries. (2003). Calculating responder days for cost-effectiveness studies. Schizophrenia Research. 60(1). 341–341. 2 indexed citations
20.
Andersen, John Sahl, et al.. (1994). A randomized play-the-winner design for multi-arm clinical trials. Communication in Statistics- Theory and Methods. 23(2). 309–323. 27 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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