Grace M. Larson

859 citations
9 papers · 543 · 1 hit paper · h-index 6

Impact in

Papers in

Grace M. Larson

9 papers receiving 511 citations

Grace M. Larson's Hit Papers

Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies 2020 · 194 citations
1940+2+4Years since publication50100150

Peers

Grace M. Larson
Comparison fields: 5 of 66
  • Social Psychology 375
  • Applied Psychology 64
  • Demography 109
  • Experimental and Cognitive Psychology 102
  • Health 53
Replace James N. Sells with:
James N. Sells United States
Stephanie S. Spielmann Canada
Erin Donovan-Kicken United States
Rachel S. T. Low New Zealand
Asuman Büyükcan-Tetik Türkiye
Wallisen Tadashi Hattori Brazil
Eric Clausell United States
Rebecca G. Burzette United States
Stefanos Mastrotheodoros Netherlands
Barbara Gormley United States
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Citations per field
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Citations per year

Countries citing papers authored by Grace M. Larson

Since Specialization
Citations

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

Fields of papers citing papers by Grace M. Larson

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Grace M. Larson. 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 Grace M. Larson. The network helps show where Grace M. Larson may publish in the future.

Co-authors

The 23 scholars most cited alongside Grace M. Larson, 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 Grace M. Larson Line = papers co-authored together Grace M. Larson links everyone, so they are left out of the graph.

All Works

9 of 9 papers shown
#Work
1 2014206
2
Machine learning uncovers the most robust self-report predictors of relationship quality across 43 longitudinal couples studies
Hit paper breakdown →
2020194
3 201541
4 200932
5 201330
6 201522
7 20206
8 20166
9 20146

About Grace M. Larson

Grace M. Larson is a scholar working on Social Psychology, Demography, Developmental and Educational Psychology, Experimental and Cognitive Psychology and Parasitology, having authored 9 papers that have together received 543 indexed citations. Recurring topics across this work include Attachment and Relationship Dynamics (4 papers), Family Dynamics and Relationships (3 papers), Identity, Memory, and Therapy (2 papers), Intergenerational Family Dynamics and Caregiving (2 papers), Gender, Labor, and Family Dynamics (1 paper), Mental Health via Writing (1 paper), Dermatological diseases and infestations (1 paper) and Marriage and Sexual Relationships (1 paper). The work is most often cited by research in Social Psychology (375 citations), Applied Psychology (64 citations), Demography (109 citations), Experimental and Cognitive Psychology (102 citations) and Health (53 citations). Grace M. Larson has collaborated with scholars based in United States, Germany and Philippines. Frequent co-authors include Eli J. Finkel, Kathleen L. Carswell, Chin Ming Hui, David A. Sbarra, Elaine O. Cheung, Lydia F. Emery, Matthias R. Mehl, Ashley E. Mason, Adriel Boals and L. Kristen Page. Their work appears in journals such as Social Psychological and Personality Science, Psychological Inquiry, Behavioral and Brain Sciences, Current Directions in Psychological Science and Emerging infectious diseases.

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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