Levi Kumle

610 citations
10 papers · 336 · 1 hit paper · h-index 5

Impact in

Papers in

Levi Kumle

8 papers receiving 334 citations

Levi Kumle's Hit Papers

Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R 2021 · 307 citations
3070+1+3Years since publication100200300

Peers

Levi Kumle
Comparison fields: 5 of 92
  • Experimental and Cognitive Psychology 96
  • Cognitive Neuroscience 126
  • Developmental and Educational Psychology 79
  • General Decision Sciences 9
  • Applied Psychology 14
Replace Yan Gu with:
Yan Gu China
Kelsey Lucca United States
Susana Ruiz Fernández Germany
Tina M. Sutton United States
Steven Samuel United Kingdom
Luke Sebanz McEllin Austria
Michelle Eskritt Canada
Antonio Román Spain
Matthew Lehet United States
Levi Kumle relative to Yan Gu China Yan Gu's profile →
Citations per field
00.5×3.7×
Yan Gu · 1×
Citations per year

Countries citing papers authored by Levi Kumle

Since Specialization
Citations

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

Fields of papers citing papers by Levi Kumle

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 20 scholars most cited alongside Levi Kumle, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Levi Kumle Line = papers co-authored together Levi Kumle links everyone, so they are left out of the graph.

All Works

10 of 10 papers shown
#Work
1
Estimating power in (generalized) linear mixed models: An open introduction and tutorial in R
Hit paper breakdown →
2021307
2 202310
3 20244
4 20234
5 20254
6 20233
7 20252
8 20202
9 20250
10 20220

About Levi Kumle

Levi Kumle is a scholar working on Cognitive Neuroscience, Public Health, Environmental and Occupational Health, Experimental and Cognitive Psychology, Human-Computer Interaction and Social Psychology, having authored 10 papers that have together received 336 indexed citations. Recurring topics across this work include Neural and Behavioral Psychology Studies (4 papers), Maternal Mental Health During Pregnancy and Postpartum (2 papers), Memory and Neural Mechanisms (2 papers), Child and Adolescent Psychosocial and Emotional Development (1 paper), Virtual Reality Applications and Impacts (1 paper), Mental Health Research Topics (1 paper), Memory Processes and Influences (1 paper) and Anxiety, Depression, Psychometrics, Treatment, Cognitive Processes (1 paper). The work is most often cited by research in Experimental and Cognitive Psychology (96 citations), Cognitive Neuroscience (126 citations), Developmental and Educational Psychology (79 citations), General Decision Sciences (9 citations) and Applied Psychology (14 citations). Levi Kumle has collaborated with scholars based in United Kingdom, Germany and United States. Frequent co-authors include Dejan Draschkow, Melissa L.‐H. Võ, Anna C. Nobre, Elaine Fox, Michelle L. Moulds, Savannah Minihan, Susanne Schweizer, Cecile D. Ladouceur, Anne‐Laura van Harmelen and Jack L. Andrews. Their work appears in journals such as Journal of Vision, Current Biology, Behavior Research Methods, JAMA Network Open and Trends in Cognitive Sciences.

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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