M. H. Gail

981 total citations · 1 hit paper
7 papers, 664 citations indexed

About

M. H. Gail is a scholar working on Statistics and Probability, Surgery and Epidemiology. According to data from OpenAlex, M. H. Gail has authored 7 papers receiving a total of 664 indexed citations (citations by other indexed papers that have themselves been cited), including 3 papers in Statistics and Probability, 2 papers in Surgery and 2 papers in Epidemiology. Recurrent topics in M. H. Gail's work include Advanced Causal Inference Techniques (2 papers), Statistical Methods and Inference (2 papers) and Statistical Methods in Clinical Trials (2 papers). M. H. Gail is often cited by papers focused on Advanced Causal Inference Techniques (2 papers), Statistical Methods and Inference (2 papers) and Statistical Methods in Clinical Trials (2 papers). M. H. Gail collaborates with scholars based in United States. M. H. Gail's co-authors include William J. Blot, Lawrence S. Engel, Joseph F. Fraumeni, J. L. Stanford, Marilie D. Gammon, Janet B. Schoenberg, Robert Dubrow, Martin J. Blaser, Thomas L. Vaughan and A. Brian West and has published in prestigious journals such as JNCI Journal of the National Cancer Institute, Biometrika and International Journal of Gynecology & Obstetrics.

In The Last Decade

M. H. Gail

7 papers receiving 632 citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Population Attributable Risks of Esophageal and Gastric Cancers

2003 525 citations Lawrence S. Engel, Thomas L. Vaughan et al. JNCI Journal of the National Cancer Institute profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
M. H. Gail United States	7	395	217	120	97	85	7	664
Aaron B. Cohen United States	14	188 0.5×	121 0.6×	154 1.3×	70 0.7×	42 0.5×	52	645
Sang Young Han South Korea	13	222 0.6×	219 1.0×	99 0.8×	59 0.6×	94 1.1×	64	604
P Guo China	15	216 0.5×	195 0.9×	241 2.0×	100 1.0×	47 0.6×	24	770
Yoon Ok Ahn South Korea	16	145 0.4×	166 0.8×	143 1.2×	57 0.6×	26 0.3×	34	705
Jane Metcalf United Kingdom	15	560 1.4×	124 0.6×	118 1.0×	62 0.6×	95 1.1×	22	1.7k
Wen‐Feng Hsu Taiwan	15	230 0.6×	315 1.5×	492 4.1×	57 0.6×	35 0.4×	37	698
F. Politi Italy	10	413 1.0×	53 0.2×	65 0.5×	83 0.9×	103 1.2×	15	1.2k
Max Parkin United Kingdom	10	159 0.4×	146 0.7×	322 2.7×	77 0.8×	15 0.2×	17	716
Megan Coombes Canada	11	91 0.2×	144 0.7×	277 2.3×	112 1.2×	10 0.1×	16	624
Georgia Vourli Greece	14	95 0.2×	90 0.4×	146 1.2×	70 0.7×	22 0.3×	37	761

Countries citing papers authored by M. H. Gail

Since Specialization

Citations

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

Fields of papers citing papers by M. H. Gail

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by M. H. Gail. 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 M. H. Gail. The network helps show where M. H. Gail may publish in the future.

Co-authorship network of co-authors of M. H. Gail

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

All Works

Sort: Min cites: Since: Top N: Style:

7 of 7 papers shown

1.

Engel, Lawrence S., Thomas L. Vaughan, Marilie D. Gammon, et al.. (2003). Population Attributable Risks of Esophageal and Gastric Cancers. JNCI Journal of the National Cancer Institute. 95(18). 1404–1413. 525 indexed citations breakdown →

2.

Pfeiffer, Ruth M., M. H. Gail, & D. Pee. (2001). Inference for covariates that accounts for ascertainment and random genetic effects in family studies. Biometrika. 88(4). 933–948. 36 indexed citations

3.

Pfeiffer, Ruth M., M. H. Gail, & Línda Morris Brown. (2000). Probability of helicobacter pylori infection based on IgG levels and other covariates using a mixture model.. PubMed. 5(5). 267–75. 12 indexed citations

4.

Byrne, Jenny, et al.. (1992). Early menopause in long-term survivors of cancer during adolescence. International Journal of Gynecology & Obstetrics. 39(3). 252–252. 8 indexed citations

5.

Gail, M. H. & Ron Brookmeyer. (1988). Methods for Projecting Course of Acquired Immunodeficiency Syndrome Epidemic1. JNCI Journal of the National Cancer Institute. 80(12). 900–911. 59 indexed citations

6.

Piantadosi, Steven, David P. Byar, & M. H. Gail. (1985). Screening Geographic Areas for Unusual Survival Experience or Stage at Diagnosis With Application to Breast and Colon Cancer. JNCI Journal of the National Cancer Institute. 75(2). 269–75. 7 indexed citations

7.

Gail, M. H., Sam Wieand, & Steven Piantadosi. (1984). Biased Estimates of Treatment Effect in Randomized Experiments with Nonlinear Regressions and Omitted Covariates. Biometrika. 71(3). 431–431. 17 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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