Jeffrey J. Starns

3.1k total citations
60 papers, 1.8k citations indexed

About

Jeffrey J. Starns is a scholar working on Cognitive Neuroscience, Social Psychology and Artificial Intelligence. According to data from OpenAlex, Jeffrey J. Starns has authored 60 papers receiving a total of 1.8k indexed citations (citations by other indexed papers that have themselves been cited), including 51 papers in Cognitive Neuroscience, 26 papers in Social Psychology and 22 papers in Artificial Intelligence. Recurrent topics in Jeffrey J. Starns's work include Memory Processes and Influences (41 papers), Deception detection and forensic psychology (24 papers) and Neural and Behavioral Psychology Studies (16 papers). Jeffrey J. Starns is often cited by papers focused on Memory Processes and Influences (41 papers), Deception detection and forensic psychology (24 papers) and Neural and Behavioral Psychology Studies (16 papers). Jeffrey J. Starns collaborates with scholars based in United States, Türkiye and Germany. Jeffrey J. Starns's co-authors include Roger Ratcliff, Jason L. Hicks, Corey N. White, Gail McKoon, Caren M. Rotello, Chad Dubé, William D. Hula, Andrew L. Cohen, Benjamin Martin and William S. Evans and has published in prestigious journals such as SHILAP Revista de lepidopterología, Psychological Review and Trends in Cognitive Sciences.

In The Last Decade

Jeffrey J. Starns

57 papers receiving 1.7k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Jeffrey J. Starns United States 22 1.6k 436 388 283 251 60 1.8k
Anjali Thapar United States 19 1.6k 1.0× 312 0.7× 190 0.5× 482 1.7× 340 1.4× 25 2.0k
Leendert van Maanen Netherlands 26 1.4k 0.9× 123 0.3× 289 0.7× 286 1.0× 299 1.2× 82 1.9k
Edward L. DeLosh United States 16 1.1k 0.7× 248 0.6× 430 1.1× 439 1.6× 564 2.2× 22 1.6k
Michael S. Pratte United States 20 1.3k 0.8× 183 0.4× 120 0.3× 280 1.0× 118 0.5× 34 1.5k
Florent Meyniel France 20 1.2k 0.8× 127 0.3× 136 0.4× 243 0.9× 174 0.7× 32 1.5k
Geoff Ward United Kingdom 23 1.4k 0.9× 169 0.4× 338 0.9× 517 1.8× 403 1.6× 49 1.8k
Joshua R. de Leeuw United States 11 729 0.5× 248 0.6× 178 0.5× 440 1.6× 247 1.0× 19 1.5k
William E. Hockley Canada 28 2.0k 1.3× 591 1.4× 428 1.1× 472 1.7× 584 2.3× 82 2.3k
Corey N. White United States 19 862 0.6× 136 0.3× 109 0.3× 331 1.2× 119 0.5× 35 1.3k
Pablo Gómez United States 22 1.7k 1.1× 201 0.5× 339 0.9× 636 2.2× 1.2k 4.9× 84 2.6k

Countries citing papers authored by Jeffrey J. Starns

Since Specialization
Citations

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

Fields of papers citing papers by Jeffrey J. Starns

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Jeffrey J. Starns. 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 Jeffrey J. Starns. The network helps show where Jeffrey J. Starns may publish in the future.

Co-authorship network of co-authors of Jeffrey J. Starns

This figure shows the co-authorship network connecting the top 25 collaborators of Jeffrey J. Starns. A scholar is included among the top collaborators of Jeffrey J. Starns 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 Jeffrey J. Starns. Jeffrey J. Starns 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.
Starns, Jeffrey J., et al.. (2025). The role of race in lineup construction.. Journal of Experimental Psychology General. 154(12). 3251–3283.
2.
Starns, Jeffrey J., et al.. (2024). Protecting the innocent in eyewitness identification: An analysis of simultaneous and ranking lineups. Journal of Memory and Language. 140. 104581–104581. 1 indexed citations
3.
Starns, Jeffrey J., et al.. (2023). Memory error speed predicts subsequent accuracy for recognition misses but not false alarms. Memory. 31(10). 1340–1351. 1 indexed citations
4.
Starns, Jeffrey J., et al.. (2018). The speed of memory errors shows the influence of misleading information: Testing the diffusion model and discrete-state models. Cognitive Psychology. 102. 21–40. 12 indexed citations
5.
Starns, Jeffrey J., et al.. (2018). A visualization technique for Bayesian reasoning. Applied Cognitive Psychology. 33(2). 234–251. 10 indexed citations
6.
Starns, Jeffrey J., et al.. (2017). Guessing versus misremembering in recognition: A comparison of continuous, two-high-threshold, and low-threshold models.. Journal of Experimental Psychology Learning Memory and Cognition. 44(4). 527–539. 5 indexed citations
7.
Kingston, John, et al.. (2015). Early Ganong effects.. ICPhS. 1 indexed citations
8.
Park, Joonkoo & Jeffrey J. Starns. (2015). The Approximate Number System Acuity Redefined: A Diffusion Model Approach. Frontiers in Psychology. 6. 1955–1955. 17 indexed citations
9.
Starns, Jeffrey J. & Jason L. Hicks. (2013). Internal reinstatement hides cuing effects in source memory tasks. Memory & Cognition. 41(7). 953–966. 6 indexed citations
10.
Starns, Jeffrey J. & Roger Ratcliff. (2013). Validating the unequal-variance assumption in recognition memory using response time distributions instead of ROC functions: A diffusion model analysis. Journal of Memory and Language. 70. 36–52. 45 indexed citations
11.
Dubé, Chad, Jeffrey J. Starns, Caren M. Rotello, & Roger Ratcliff. (2012). Beyond ROC curvature: Strength effects and response time data support continuous-evidence models of recognition memory. Journal of Memory and Language. 67(3). 389–406. 37 indexed citations
12.
Starns, Jeffrey J., Roger Ratcliff, & Gail McKoon. (2011). Evaluating the unequal-variance and dual-process explanations of zROC slopes with response time data and the diffusion model. Cognitive Psychology. 64(1-2). 1–34. 81 indexed citations
13.
Starns, Jeffrey J. & Roger Ratcliff. (2011). Age-related differences in diffusion model boundary optimality with both trial-limited and time-limited tasks. Psychonomic Bulletin & Review. 19(1). 139–145. 59 indexed citations
14.
Ratcliff, Roger & Jeffrey J. Starns. (2009). Modeling confidence and response time in recognition memory.. Psychological Review. 116(1). 59–83. 176 indexed citations
15.
Starns, Jeffrey J. & Jason L. Hicks. (2008). Context attributes in memory are bound to item information, but not to one another. Psychonomic Bulletin & Review. 15(2). 309–314. 27 indexed citations
16.
Starns, Jeffrey J., et al.. (2008). Source memory for unrecognized items: Predictions from multivariate signal detection theory. Memory & Cognition. 36(1). 1–8. 38 indexed citations
17.
Starns, Jeffrey J. & Jason L. Hicks. (2005). Source Dimensions Are Retrieved Independently in Multidimensional Monitoring Tasks.. Journal of Experimental Psychology Learning Memory and Cognition. 31(6). 1213–1220. 45 indexed citations
18.
Hicks, Jason L. & Jeffrey J. Starns. (2005). False memories lack perceptual detail: Evidence from implicit word-stem completion and perceptual identification tests. Journal of Memory and Language. 52(3). 309–321. 36 indexed citations
19.
Hicks, Jason L. & Jeffrey J. Starns. (2004). Retrieval-induced forgetting occurs in tests of item recognition. Psychonomic Bulletin & Review. 11(1). 125–130. 105 indexed citations
20.
Starns, Jeffrey J. & Jason L. Hicks. (2004). Episodic generation can cause semantic forgetting: Retrieval-induced forgetting of false memories. Memory & Cognition. 32(4). 602–609. 33 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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