Stephanie Lane

1.6k total citations
26 papers, 1.1k citations indexed

About

Stephanie Lane is a scholar working on Experimental and Cognitive Psychology, Cognitive Neuroscience and Control and Systems Engineering. According to data from OpenAlex, Stephanie Lane has authored 26 papers receiving a total of 1.1k indexed citations (citations by other indexed papers that have themselves been cited), including 10 papers in Experimental and Cognitive Psychology, 7 papers in Cognitive Neuroscience and 5 papers in Control and Systems Engineering. Recurrent topics in Stephanie Lane's work include Mental Health Research Topics (10 papers), Functional Brain Connectivity Studies (7 papers) and Fault Detection and Control Systems (5 papers). Stephanie Lane is often cited by papers focused on Mental Health Research Topics (10 papers), Functional Brain Connectivity Studies (7 papers) and Fault Detection and Control Systems (5 papers). Stephanie Lane collaborates with scholars based in United States, United Kingdom and Netherlands. Stephanie Lane's co-authors include Kathleen M. Gates, Patrick J. Curran, Howard E. Barbaree, Sierra A. Bainter, James S. McGinley, E.B. Martin, A.J. Morris, Aidan G.C. Wright, Adriene M. Beltz and Kelly S. Giovanello and has published in prestigious journals such as Journal of Consulting and Clinical Psychology, Biological Psychiatry and Journal of Bacteriology.

In The Last Decade

Stephanie Lane

21 papers receiving 1.0k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Stephanie Lane United States 13 478 288 249 176 153 26 1.1k
Patrí­cia Arriaga Portugal 22 195 0.4× 160 0.6× 156 0.6× 597 3.4× 36 0.2× 97 1.3k
Woo Sik Jung South Korea 12 270 0.6× 366 1.3× 133 0.5× 187 1.1× 30 0.2× 50 1.2k
Paul Panek United States 17 126 0.3× 126 0.4× 182 0.7× 363 2.1× 82 0.5× 98 1.2k
Zhuo Rachel Han China 23 179 0.4× 851 3.0× 355 1.4× 407 2.3× 219 1.4× 101 1.6k
José Vasconcelos-Raposo Portugal 22 154 0.3× 195 0.7× 134 0.5× 441 2.5× 18 0.1× 104 1.3k
Peter Franz United States 13 193 0.4× 661 2.3× 160 0.6× 194 1.1× 18 0.1× 54 1.0k
James E. McLean United States 25 359 0.8× 350 1.2× 494 2.0× 104 0.6× 21 0.1× 106 1.8k
Diana Kornbrot United Kingdom 20 339 0.7× 98 0.3× 482 1.9× 120 0.7× 16 0.1× 59 1.1k
ANTHONY DAVIDS United States 21 239 0.5× 570 2.0× 143 0.6× 264 1.5× 71 0.5× 102 1.6k
Min Hane Aung United Kingdom 19 565 1.2× 89 0.3× 179 0.7× 207 1.2× 13 0.1× 40 1.5k

Countries citing papers authored by Stephanie Lane

Since Specialization
Citations

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

Fields of papers citing papers by Stephanie Lane

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authorship network of co-authors of Stephanie Lane

This figure shows the co-authorship network connecting the top 25 collaborators of Stephanie Lane. A scholar is included among the top collaborators of Stephanie Lane 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 Stephanie Lane. Stephanie Lane 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.
Guillory, Jamie, Stephanie Lane, Annice Kim, et al.. (2024). Content analysis of conversations on Reddit: reactions to FDA’s ENDS prioritized enforcement policy. Frontiers in Communication. 9. 1348158–1348158.
2.
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Lane, Stephanie, et al.. (2022). Unsupervised classification reveals consistency and degeneracy in neural network patterns of emotion. Social Cognitive and Affective Neuroscience. 17(11). 995–1006. 15 indexed citations
4.
Weigard, Alexander, Stephanie Lane, Kathleen M. Gates, & Adriene M. Beltz. (2021). The influence of autoregressive relation strength and search strategy on directionality recovery in group iterative multiple model estimation.. Psychological Methods. 28(2). 379–400. 12 indexed citations
5.
Porter, Daniel, et al.. (2020). Initial validation of the trust of automated systems test (TOAST). The Journal of Social Psychology. 160(6). 735–750. 47 indexed citations
6.
Wright, Aidan G.C., Kathleen M. Gates, Cara Arizmendi, et al.. (2019). Focusing personality assessment on the person: Modeling general, shared, and person specific processes in personality and psychopathology.. Psychological Assessment. 31(4). 502–515. 71 indexed citations
7.
Lane, Stephanie. (2019). Regularized Structural Equation Modeling for Individual-Level Directed Functional Connectivity. Carolina Digital Repository (University of North Carolina at Chapel Hill). 2 indexed citations
8.
Lane, Stephanie, et al.. (2018). Uncovering general, shared, and unique temporal patterns in ambulatory assessment data.. Psychological Methods. 24(1). 54–69. 103 indexed citations
9.
Lane, Stephanie & Kathleen M. Gates. (2017). Evaluating the Use of the Automated Unified Structural Equation Model for Daily Diary Data. Multivariate Behavioral Research. 52(1). 126–127. 2 indexed citations
10.
Wright, Aidan G.C., Kathleen M. Gates, Cara Arizmendi, et al.. (2017). Group Iterative Multiple Model Estimation (GIMME) for Personalized Personality Models. OSF Preprints (OSF Preprints).
11.
Lane, Stephanie & Kathleen M. Gates. (2017). Automated Selection of Robust Individual-Level Structural Equation Models for Time Series Data. Structural Equation Modeling A Multidisciplinary Journal. 24(5). 768–782. 47 indexed citations
12.
Price, Rebecca B., Stephanie Lane, Kathleen M. Gates, et al.. (2016). Parsing Heterogeneity in the Brain Connectivity of Depressed and Healthy Adults During Positive Mood. Biological Psychiatry. 81(4). 347–357. 78 indexed citations
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Lane, Stephanie, Joseph C. Franklin, & Patrick J. Curran. (2013). Clarifying the nature of startle habituation using latent curve modeling. International Journal of Psychophysiology. 88(1). 55–63. 24 indexed citations
15.
Curran, Patrick J., Howard E. Barbaree, Sierra A. Bainter, Stephanie Lane, & James S. McGinley. (2013). The separation of between-person and within-person components of individual change over time: A latent curve model with structured residuals.. Journal of Consulting and Clinical Psychology. 82(5). 879–894. 350 indexed citations
16.
Curran, Patrick J., Taehun Lee, Howard E. Barbaree, Stephanie Lane, & Robert C. MacCallum. (2012). Disaggregating within-person and between-person effects in multilevel and structural equation growth models.. 40 indexed citations
17.
King, Rodney A., et al.. (2011). Newly Discovered Antiterminator RNAs in Bacteriophage. Journal of Bacteriology. 193(20). 5784–5792. 3 indexed citations
18.
Lane, Stephanie, et al.. (2010). Comparison of three cannulas for hysterosalpingography: a prospective, randomized study. Fertility and Sterility. 94(4). S211–S211.
19.
Martin, E.B., Julian Morris, & Stephanie Lane. (2002). Monitoring process manufacturing performance. IEEE Control Systems. 22(5). 26–39. 18 indexed citations
20.
Lane, Stephanie, et al.. (2001). Performance monitoring of a multi-product semi-batch process. Journal of Process Control. 11(1). 1–11. 95 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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