Bruce Ratner

1.9k total citations · 1 hit paper
12 papers, 1.3k citations indexed

About

Bruce Ratner is a scholar working on Information Systems, Marketing and Strategy and Management. According to data from OpenAlex, Bruce Ratner has authored 12 papers receiving a total of 1.3k indexed citations (citations by other indexed papers that have themselves been cited), including 2 papers in Information Systems, 2 papers in Marketing and 1 paper in Strategy and Management. Recurrent topics in Bruce Ratner's work include Data Mining Algorithms and Applications (2 papers), Relativity and Gravitational Theory (1 paper) and Advanced Statistical Methods and Models (1 paper). Bruce Ratner is often cited by papers focused on Data Mining Algorithms and Applications (2 papers), Relativity and Gravitational Theory (1 paper) and Advanced Statistical Methods and Models (1 paper). Bruce Ratner collaborates with scholars based in . Bruce Ratner's co-authors include Christopher Davies and Stephen H. Day and has published in prestigious journals such as Journal of Targeting Measurement and Analysis for Marketing and Medical Entomology and Zoology.

In The Last Decade

Bruce Ratner

10 papers receiving 1.3k 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.

The correlation coefficient: Its values range between +1/−1, or do they?

2009 1.1k citations Bruce Ratner Journal of Targeting Measurement and Analysis for Marketing profile →

Peers

Bruce Ratner

GPC

AI

EE

SPS

BE

C. Spearman

Rajkumar Dhakar India

Hui Hui China

H. Senter United States

Habshah Midi Malaysia

Alysha De Livera Australia

Jaime L. Speiser United States

Hui‐Zhen Fu China

Dae Hyun Kim South Korea

Marie‐Therese Puth Germany

C. Spearman

Bruce Ratner

134 ×1.1

GPC

224 ×2.4

AI

60 ×0.7

EE

72 ×1.0

SPS

51 ×0.7

BE

Citations per year, relative to Bruce Ratner Bruce Ratner (= 1×) peers C. Spearman

Countries citing papers authored by Bruce Ratner

Since Specialization

Citations

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

Fields of papers citing papers by Bruce Ratner

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Bruce Ratner

This figure shows the co-authorship network connecting the top 25 collaborators of Bruce Ratner. A scholar is included among the top collaborators of Bruce Ratner 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 Bruce Ratner. Bruce Ratner 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:

12 of 12 papers shown

1.

Ratner, Bruce. (2017). Statistical and Machine-Learning Data Mining, Third Edition. 35 indexed citations

2.

Ratner, Bruce. (2017). Logistic Regression: The Workhorse of Response Modeling. 105–150. 1 indexed citations

3.

Ratner, Bruce, Stephen H. Day, & Christopher Davies. (2011). Statistical and Machine-Learning Data Mining. 24 indexed citations

4.

Ratner, Bruce. (2011). Statistical and Machine-Learning Data Mining: Techniques for Better Predictive Modeling and Analysis of Big Data, Second Edition. 9 indexed citations

5.

Ratner, Bruce. (2010). Variable selection methods in regression: Ignorable problem, outing notable solution. Journal of Targeting Measurement and Analysis for Marketing. 18(1). 65–75. 69 indexed citations

6.

Ratner, Bruce. (2009). Pythagoras: Everyone knows his famous theorem, but not who discovered it 1000 years before him. Journal of Targeting Measurement and Analysis for Marketing. 17(3). 229–242. 6 indexed citations

7.

Ratner, Bruce. (2009). The correlation coefficient: Its values range between +1/−1, or do they?. Journal of Targeting Measurement and Analysis for Marketing. 17(2). 139–142. 1080 indexed citations breakdown →

8.

Ratner, Bruce. (2003). Statistical Modeling and Analysis for Database Marketing: Effective Techniques for Mining Big Data. Medical Entomology and Zoology. 40 indexed citations

9.

Ratner, Bruce. (2003). Statistical Modeling and Analysis for Database Marketing. 33 indexed citations

10.

Ratner, Bruce. (2002). Rapid statistical calculations for determining the success of marketing campaigns. Journal of Targeting Measurement and Analysis for Marketing. 10(4). 385–390. 1 indexed citations

11.

Ratner, Bruce. (2001). Finding the best variables for direct marketing models. Journal of Targeting Measurement and Analysis for Marketing. 9(3). 270–296. 1 indexed citations

12.

Ratner, Bruce. (2001). Identifying the best customers: Descriptive, predictive and look-alike profiling. Journal of Targeting Measurement and Analysis for Marketing. 10(1). 66–78. 2 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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