C. T. Yu

926 total citations
49 papers, 676 citations indexed

About

C. T. Yu is a scholar working on Developmental and Educational Psychology, Cognitive Neuroscience and Psychiatry and Mental health. According to data from OpenAlex, C. T. Yu has authored 49 papers receiving a total of 676 indexed citations (citations by other indexed papers that have themselves been cited), including 35 papers in Developmental and Educational Psychology, 34 papers in Cognitive Neuroscience and 19 papers in Psychiatry and Mental health. Recurrent topics in C. T. Yu's work include Behavioral and Psychological Studies (35 papers), Autism Spectrum Disorder Research (32 papers) and Family and Disability Support Research (13 papers). C. T. Yu is often cited by papers focused on Behavioral and Psychological Studies (35 papers), Autism Spectrum Disorder Research (32 papers) and Family and Disability Support Research (13 papers). C. T. Yu collaborates with scholars based in Canada, China and United States. C. T. Yu's co-authors include Garry L. Martin, Toby L. Martin, Javier Virúes‐Ortega, Kendra Thomson, Tricia Vause, Jeanette J. A. Holden, Hélène Ouellette‐Kuntz, M. Breitenbach, Helen Coo and Albert E. Chudley and has published in prestigious journals such as Journal of Autism and Developmental Disorders, Journal of Applied Behavior Analysis and Research in autism spectrum disorders.

In The Last Decade

C. T. Yu

45 papers receiving 613 citations

Peers — A (Enhanced Table)

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

Name h Career Trend Papers Cites
C. T. Yu Canada 16 504 378 257 200 71 49 676
Daniel Crimmins United States 13 538 1.1× 553 1.5× 395 1.5× 231 1.2× 80 1.1× 31 855
Şerife Yücesoy Özkan Türkiye 9 558 1.1× 373 1.0× 409 1.6× 142 0.7× 137 1.9× 37 753
Brianne Tomaszewski United States 13 698 1.4× 383 1.0× 527 2.1× 188 0.9× 170 2.4× 30 913
Victoria Shea United States 10 710 1.4× 340 0.9× 501 1.9× 205 1.0× 222 3.1× 16 887
Jeffrey M. Chan United States 18 653 1.3× 537 1.4× 460 1.8× 141 0.7× 125 1.8× 25 851
Tracy J. Raulston United States 14 401 0.8× 230 0.6× 354 1.4× 92 0.5× 111 1.6× 36 542
Hsu-Min Chiang United States 15 653 1.3× 293 0.8× 408 1.6× 177 0.9× 199 2.8× 21 854
Lynn Adams United States 9 497 1.0× 262 0.7× 327 1.3× 126 0.6× 153 2.2× 14 617
Stephanie Gerow United States 16 600 1.2× 420 1.1× 393 1.5× 167 0.8× 64 0.9× 41 733
Einar T. Ingvarsson United States 20 641 1.3× 755 2.0× 227 0.9× 239 1.2× 107 1.5× 48 916

Countries citing papers authored by C. T. Yu

Since Specialization
Citations

This map shows the geographic impact of C. T. Yu'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 C. T. Yu with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites C. T. Yu more than expected).

Fields of papers citing papers by C. T. Yu

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by C. T. Yu. 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 C. T. Yu. The network helps show where C. T. Yu may publish in the future.

Co-authorship network of co-authors of C. T. Yu

This figure shows the co-authorship network connecting the top 25 collaborators of C. T. Yu. A scholar is included among the top collaborators of C. T. Yu 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 C. T. Yu. C. T. Yu 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.
Li, Li, Hai Du, Xinyi Li, et al.. (2025). A study of brain function changes in patients with trigeminal neuralgia of different laterality based on rs-fMRI. Journal of Oral & Facial Pain and Headache. 39(1). 148–156.
2.
Yu, C. T., et al.. (2017). Effects of computer‐aided instruction on the implementation of the MSWO stimulus preference assessment. Behavioral Interventions. 33(1). 56–68. 10 indexed citations
3.
Virúes‐Ortega, Javier, et al.. (2013). Prediction of treatment outcomes and longitudinal analysis in children with autism undergoing intensive behavioral intervention. International Journal of Clinical and Health Psychology. 13(2). 91–100. 56 indexed citations
4.
Martin, Garry L., et al.. (2012). TEACHING CHILDREN WITH AUTISM SPECTRUM DISORDER TO MAND FOR INFORMATION USING “WHICH?”. Journal of Applied Behavior Analysis. 45(4). 865–870. 9 indexed citations
5.
Martin, Garry L., et al.. (2012). Teaching Children with Autism Spectrum Disorder to Mand “Where?”. Journal of Behavioral Education. 21(4). 273–294. 10 indexed citations
6.
Thomson, Kendra, et al.. (2012). Evaluation of a self-instructional package for teaching tutors to conduct discrete-trials teaching with children with autism. Research in autism spectrum disorders. 6(3). 1073–1082. 20 indexed citations
7.
Martin, Garry L. & C. T. Yu. (2010). A Response to Stewart, McElwee, and Ming. The Behavior Analyst. 33(2). 231–233. 1 indexed citations
8.
Malisza, Krisztina L., Jeanette J. A. Holden, Kristjan Paulson, et al.. (2010). Functional Evaluation of Hidden Figures Object Analysis in Children with Autistic Disorder. Journal of Autism and Developmental Disorders. 41(1). 13–22. 16 indexed citations
9.
Yu, C. T., et al.. (2010). ON THE RELATION BETWEEN REINFORCER EFFICACY AND PREFERENCE. Journal of Applied Behavior Analysis. 43(1). 95–100. 28 indexed citations
10.
Thomson, Kendra, et al.. (2009). Instructing individuals to deliver discrete-trials teaching to children with autism spectrum disorders: A review. Research in autism spectrum disorders. 3(3). 590–606. 34 indexed citations
11.
Yu, C. T., et al.. (2009). The Influence of Different Kinds of Reference Groups on Self-brand Connections. Acta Psychologica Sinica. 41(2). 156–166. 5 indexed citations
12.
Yu, C. T., et al.. (2008). Discrimination Skills Predict Effective Preference Assessment Methods for Adults with Developmental Disabilities. Education and training in developmental disabilities. 43(3). 388–396. 5 indexed citations
13.
Martin, Garry L., et al.. (2007). Predicting Learning Ability of People With Intellectual Disabilities: Assessment of Basic Learning Abilities Test Versus Caregivers' Predictions. American Journal on Mental Retardation. 112(2). 130–130. 8 indexed citations
14.
Martin, Garry L., et al.. (2007). Does ABLA Test Performance on the ABLA Test Predict Picture Receptive Name Recognition with Persons with Severe Developmental Disabilities?. The Analysis of Verbal Behavior. 23(1). 35–39. 6 indexed citations
15.
Yu, C. T., et al.. (2006). Factors Affecting Parenting Stress Among Biologically Vulnerable Toddlers. Issues in Comprehensive Pediatric Nursing. 29(3). 131–156. 32 indexed citations
16.
Martin, Toby L., et al.. (2006). On choice, preference, and preference for choice.. The Behavior Analyst Today. 7(2). 234–241. 15 indexed citations
18.
Ouellette‐Kuntz, Hélène, Helen Coo, C. T. Yu, et al.. (2006). Prevalence of Pervasive Developmental Disorders in Two Canadian Provinces. Journal of Policy and Practice in Intellectual Disabilities. 3(3). 164–172. 30 indexed citations
19.
Yu, C. T., et al.. (2005). Predicting the Relative Efficacy of Verbal, Pictorial, and Tangible Stimuli for Assessing Preferences of Leisure Activities. American Journal on Mental Retardation. 110(2). 145–145. 17 indexed citations
20.
Martin, Toby L., et al.. (2004). Visual–Visual Nonidentity Matching Assessment: A Worthwhile Addition to the Assessment of Basic Learning Abilities Test. American Journal on Mental Retardation. 109(1). 44–44. 12 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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