Michael A. Stadler

2.5k total citations
33 papers, 1.9k citations indexed

About

Michael A. Stadler is a scholar working on Cognitive Neuroscience, Developmental and Educational Psychology and Social Psychology. According to data from OpenAlex, Michael A. Stadler has authored 33 papers receiving a total of 1.9k indexed citations (citations by other indexed papers that have themselves been cited), including 17 papers in Cognitive Neuroscience, 11 papers in Developmental and Educational Psychology and 6 papers in Social Psychology. Recurrent topics in Michael A. Stadler's work include Child and Animal Learning Development (7 papers), Memory Processes and Influences (6 papers) and Neural and Behavioral Psychology Studies (6 papers). Michael A. Stadler is often cited by papers focused on Child and Animal Learning Development (7 papers), Memory Processes and Influences (6 papers) and Neural and Behavioral Psychology Studies (6 papers). Michael A. Stadler collaborates with scholars based in United States, United Kingdom and Germany. Michael A. Stadler's co-authors include Peter A. Frensch, Henry L. Roediger, Kathleen B. McDermott, Monica Fabiani, Gordon D. Logan, Peter D. Kruse, Nelson Cowan, Noelle L. Wood, John­–Dylan Haynes and G. Roth and has published in prestigious journals such as Journal of Neurophysiology, Scientific Reports and Journal of Cognitive Neuroscience.

In The Last Decade

Michael A. Stadler

30 papers receiving 1.8k citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
Michael A. Stadler United States 17 1.5k 687 630 282 174 33 1.9k
Dirk Vorberg Germany 22 1.8k 1.1× 525 0.8× 349 0.6× 445 1.6× 134 0.8× 42 2.1k
Joachim Hoffmann Germany 31 2.1k 1.4× 754 1.1× 1000 1.6× 446 1.6× 99 0.6× 93 2.6k
Catherine Morris United States 9 1.3k 0.9× 1.1k 1.6× 386 0.6× 599 2.1× 360 2.1× 13 2.2k
Gregory V. Jones United Kingdom 21 1.2k 0.8× 543 0.8× 294 0.5× 481 1.7× 255 1.5× 80 1.7k
Hubert D. Zimmer Germany 32 2.3k 1.5× 847 1.2× 933 1.5× 725 2.6× 200 1.1× 114 3.1k
Richard Cooper United Kingdom 22 885 0.6× 540 0.8× 432 0.7× 358 1.3× 285 1.6× 96 1.7k
Timothy L. Hubbard United States 30 2.3k 1.5× 572 0.8× 1.1k 1.8× 1.0k 3.6× 109 0.6× 107 3.0k
John G. Seamon United States 25 1.9k 1.2× 440 0.6× 908 1.4× 488 1.7× 280 1.6× 60 2.3k
Mark John United States 11 774 0.5× 548 0.8× 320 0.5× 218 0.8× 284 1.6× 30 1.5k
Ira Fischler United States 26 2.2k 1.4× 1.3k 1.9× 364 0.6× 660 2.3× 303 1.7× 53 2.7k

Countries citing papers authored by Michael A. Stadler

Since Specialization
Citations

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

Fields of papers citing papers by Michael A. Stadler

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Michael A. Stadler. 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 Michael A. Stadler. The network helps show where Michael A. Stadler may publish in the future.

Co-authorship network of co-authors of Michael A. Stadler

This figure shows the co-authorship network connecting the top 25 collaborators of Michael A. Stadler. A scholar is included among the top collaborators of Michael A. Stadler 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 Michael A. Stadler. Michael A. Stadler 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.
Stadler, Michael A., Sizheng Steven Zhao, & John Bowes. (2024). A review of the advances in understanding the genetic basis of spondylarthritis and emerging clinical benefit. Best Practice & Research Clinical Rheumatology. 38(4). 101982–101982. 1 indexed citations
2.
Hum, Ryan Malcolm, Seema Sharma, Michael A. Stadler, et al.. (2023). Using Polygenic Risk Scores to Aid Diagnosis of Patients With Early Inflammatory Arthritis: Results From the Norfolk Arthritis Register. Arthritis & Rheumatology. 76(5). 696–703. 6 indexed citations
3.
Stadler, Michael A., Nick Dand, Deepak R. Jadon, et al.. (2021). Application of information theoretic feature selection and machine learning methods for the development of genetic risk prediction models. Scientific Reports. 11(1). 23335–23335. 19 indexed citations
4.
Stadler, Michael A.. (2020). 5 Cognitive Linguistics II: Image Schemata and Conceptual Metonymy. ISBN. 139–191.
5.
Schachtman, Todd R., et al.. (2010). Strategic behavior without awareness? Effects of implicit learning in the Eriksen flanker paradigm. Memory & Cognition. 38(2). 197–205. 22 indexed citations
6.
Stadler, Michael A., et al.. (2006). Gestaltübergänge in der Musik: vom Wandel der Ordnungsprinzipien. Social Science Open Access Repository (GESIS – Leibniz Institute for the Social Sciences). 14. 274–301.
7.
Fabiani, Monica, et al.. (2000). True But Not False Memories Produce a Sensory Signature in Human Lateralized Brain Potentials. Journal of Cognitive Neuroscience. 12(6). 941–949. 90 indexed citations
8.
Stadler, Michael A., et al.. (2000). Is There Cross-format Transfer in Implicit Invariance Learning?. The Quarterly Journal of Experimental Psychology Section A. 53(1). 235–245. 4 indexed citations
9.
Stadler, Michael A., Henry L. Roediger, & Kathleen B. McDermott. (1999). Norms for word lists that create false memories. Memory & Cognition. 27(3). 494–500. 401 indexed citations
10.
Stadler, Michael A. & Peter A. Frensch. (1998). Handbook of implicit learning. 394 indexed citations
11.
Stadler, Michael A. & Henry L. Roediger. (1998). The question of awareness in research on implicit learning. 29 indexed citations
12.
Dienes, Zoltán, et al.. (1997). Commentary. Psychonomic Bulletin & Review. 4(4). 587–591. 8 indexed citations
13.
Wood, Noelle L., Michael A. Stadler, & Nelson Cowan. (1997). Is there implicit memory without attention? A reexamination of task demands in Eich’s (1984) procedure. Memory & Cognition. 25(6). 772–779. 31 indexed citations
14.
Stadler, Michael A., et al.. (1996). Varieties of positive and negative priming. Psychonomic Bulletin & Review. 3(1). 87–90. 45 indexed citations
15.
Johnstone, Brick, Kristi Erdal, & Michael A. Stadler. (1995). The relationship between the Wechsler Memory Scale—Revised (WMS-R) Attention index and putative measures of Attention. Journal of Clinical Psychology in Medical Settings. 2(2). 195–204. 9 indexed citations
16.
Stadler, Michael A.. (1993). Implicit serial learning: Questions inspired by Hebb (1961). Memory & Cognition. 21(6). 819–827. 107 indexed citations
17.
Stadler, Michael A.. (1992). Statistical structure and implicit serial learning.. Journal of Experimental Psychology Learning Memory and Cognition. 18(2). 318–327. 113 indexed citations
18.
Stadler, Michael A.. (1989). On learning complex procedural knowledge.. Journal of Experimental Psychology Learning Memory and Cognition. 15(6). 1061–1069. 35 indexed citations
19.
Stadler, Michael A.. (1989). Chunking and implicit pattern learning in a serial reaction time task. Purdue e-Pubs (Purdue University System). 2 indexed citations
20.
Eggemeier, F. Thomas & Michael A. Stadler. (1984). Subjective Workload Assessment in a Spatial Memory Task. Proceedings of the Human Factors Society Annual Meeting. 28(8). 680–684. 4 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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