Conor V. Dolan

20.5k total citations · 3 hit papers
231 papers, 10.0k citations indexed

About

Conor V. Dolan is a scholar working on Experimental and Cognitive Psychology, Genetics and Statistics and Probability. According to data from OpenAlex, Conor V. Dolan has authored 231 papers receiving a total of 10.0k indexed citations (citations by other indexed papers that have themselves been cited), including 96 papers in Experimental and Cognitive Psychology, 75 papers in Genetics and 37 papers in Statistics and Probability. Recurrent topics in Conor V. Dolan's work include Cognitive Abilities and Testing (80 papers), Genetic Associations and Epidemiology (53 papers) and Genetic Mapping and Diversity in Plants and Animals (41 papers). Conor V. Dolan is often cited by papers focused on Cognitive Abilities and Testing (80 papers), Genetic Associations and Epidemiology (53 papers) and Genetic Mapping and Diversity in Plants and Animals (41 papers). Conor V. Dolan collaborates with scholars based in Netherlands, United States and United Kingdom. Conor V. Dolan's co-authors include Dorret I. Boomsma, Maurits W. van der Molen, Mariëtte Huizinga, Jelte M. Wicherts, Han L. J. van der Maas, Sophie van der Sluis, Peter C. M. Molenaar, Daniëlle Posthuma, Hilde M. Huizenga and Eske M. Derks and has published in prestigious journals such as Journal of Personality and Social Psychology, Nature Genetics and SHILAP Revista de lepidopterología.

In The Last Decade

Conor V. Dolan

224 papers receiving 9.6k citations

Hit Papers

align trajectories

What are hit papers?

Hit papers significantly outperform the citation benchmark for their cohort. A paper qualifies if it has ≥500 total citations, achieves ≥1.5× the top-1% citation threshold for papers in the same subfield and year (this is the minimum needed to enter the top 1%, not the average within it), or reaches the top citation threshold in at least one of its specific research topics.

Age-related change in executive function: Developmental trends and a latent variable analysis

2006 1.2k citations Conor V. Dolan et al. profile →
A dynamical model of general intelligence: The positive manifold of intelligence by mutualism.

2006 645 citations Han L. J. van der Maas, Conor V. Dolan et al. profile →
A solution to dependency: using multilevel analysis to accommodate nested data

2014 428 citations Matthijs Verhage, Conor V. Dolan et al. profile →

Peers — A (Enhanced Table)

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

Name	h						Papers	Cites
Conor V. Dolan Netherlands	51	3.7k	2.3k	1.8k	1.3k	1.2k	231	10.0k
Timothy C. Bates United Kingdom	44	2.5k 0.7×	1.3k 0.6×	1.6k 0.9×	1.1k 0.8×	1.2k 1.0×	187	7.6k
John J. McArdle United States	59	3.4k 0.9×	2.5k 1.1×	1.1k 0.6×	588 0.4×	1.0k 0.8×	157	12.2k
Elliot M. Tucker–Drob United States	49	2.9k 0.8×	1.6k 0.7×	1.7k 0.9×	1.1k 0.8×	764 0.6×	160	8.3k
Peter C. M. Molenaar United States	46	4.0k 1.1×	1.6k 0.7×	2.7k 1.5×	470 0.3×	846 0.7×	250	9.4k
Emilio Ferrer United States	46	2.4k 0.7×	2.2k 0.9×	1.7k 0.9×	328 0.2×	875 0.7×	161	7.2k
John C. Loehlin United States	42	5.8k 1.6×	3.4k 1.5×	1.1k 0.6×	1.7k 1.3×	1.4k 1.1×	162	12.1k
Philip A. Vernon Canada	56	3.7k 1.0×	4.4k 1.9×	1.6k 0.9×	581 0.4×	1.0k 0.8×	181	9.7k
John R. Nesselroade United States	56	4.6k 1.3×	3.1k 1.4×	1.3k 0.7×	466 0.3×	1.4k 1.1×	170	13.5k
Wendy Johnson United Kingdom	49	4.7k 1.3×	4.5k 2.0×	2.0k 1.1×	963 0.7×	1.0k 0.8×	189	13.3k
Mijke Rhemtulla United States	32	2.6k 0.7×	1.9k 0.8×	1.2k 0.6×	388 0.3×	459 0.4×	83	7.3k

Countries citing papers authored by Conor V. Dolan

Since Specialization

Citations

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

Fields of papers citing papers by Conor V. Dolan

Since Specialization

Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Conor V. Dolan. 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 Conor V. Dolan. The network helps show where Conor V. Dolan may publish in the future.

Co-authorship network of co-authors of Conor V. Dolan

This figure shows the co-authorship network connecting the top 25 collaborators of Conor V. Dolan. A scholar is included among the top collaborators of Conor V. Dolan 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 Conor V. Dolan. Conor V. Dolan is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

Sort: Min cites: Since: Top N: Style:

20 of 20 papers shown

1.

Dolan, Conor V., David H. Wilson, Lannie Ligthart, et al.. (2025). Genetic and environmental contributions to variation in plasma phosphorylated tau 217. Alzheimer s & Dementia. 21(11). e70906–e70906.

2.

Dolan, Conor V., Jouke‐Jan Hottenga, René Pool, et al.. (2025). Unidirectional and bidirectional causation between smoking and blood DNA methylation: evidence from twin-based Mendelian randomisation. European Journal of Epidemiology. 40(1). 55–69.

3.

Bergen, Elsje van, Maurits Masselink, Catharina A. Hartman, et al.. (2024). Are Genetic and Environmental Risk Factors for Psychopathology Amplified in Children with Below-Average Intelligence? A Population-Based Twin Study. Behavior Genetics. 54(3). 278–289.

4.

Verhulst, Brad, Yi Zhou, Luís Fernando Silva Castro-de-Araujo, et al.. (2024). Using Instrumental Variables to Measure Causation over Time in Cross-Lagged Panel Models. Multivariate Behavioral Research. 59(2). 342–370. 3 indexed citations

5.

Dolan, Conor V., et al.. (2023). Self‐control and grit are associated with school performance mainly because of shared genetic effects. SHILAP Revista de lepidopterología. 3(2). e12159–e12159. 6 indexed citations

6.

Dolan, Conor V., et al.. (2023). Integrating Cross-Lagged Panel Models with Instrumental Variables to Extend the Temporal Generalizability of Causal Inference. Multivariate Behavioral Research. 58(1). 148–149. 3 indexed citations

7.

Slob, Elise M. A., Cristina Longo, Susanne J. H. Vijverberg, et al.. (2022). Persistence of parental‐reported asthma at early ages: A longitudinal twin study. Pediatric Allergy and Immunology. 33(3). e13762–e13762. 7 indexed citations

8.

Castro-de-Araujo, Luís Fernando Silva, et al.. (2022). MR-DoC2: Bidirectional Causal Modeling with Instrumental Variables and Data from Relatives. Behavior Genetics. 53(1). 63–73. 10 indexed citations

9.

Bergen, Elsje van, et al.. (2022). Intergenerational transmission of body mass index and associations with educational attainment. BMC Public Health. 22(1). 890–890. 3 indexed citations

10.

Hottenga, Jouke‐Jan, Michael D. Hunter, Eveline L. de Zeeuw, et al.. (2021). Multilevel Twin Models: Geographical Region as a Third Level Variable. Behavior Genetics. 51(3). 319–330. 4 indexed citations

11.

Hu, Mandy X., Yuri Milaneschi, Femke Lamers, et al.. (2019). The association of depression and anxiety with cardiac autonomic activity: The role of confounding effects of antidepressants. Depression and Anxiety. 36(12). 1163–1172. 41 indexed citations

12.

Franić, Sanja, et al.. (2013). Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.. Psychological Methods. 18(3). 406–433. 32 indexed citations

13.

Molenaar, Dylan & Conor V. Dolan. (2012). Substantively motivated extensions of the traditional latent trait model. UvA-DARE (University of Amsterdam). 67(3). 48–57. 2 indexed citations

14.

Molenaar, Dylan, Conor V. Dolan, & Han L. J. van der Maas. (2011). Modeling Ability Differentiation in the Second-Order Factor Model. Structural Equation Modeling A Multidisciplinary Journal. 18(4). 578–594. 18 indexed citations

15.

Sluis, Sophie van der, Matthijs Verhage, Daniëlle Posthuma, & Conor V. Dolan. (2010). Phenotypic Complexity, Measurement Bias, and Poor Phenotypic Resolution Contribute to the Missing Heritability Problem in Genetic Association Studies. PLoS ONE. 5(11). e13929–e13929. 98 indexed citations

16.

Hessen, David J. & Conor V. Dolan. (2008). Heteroscedastic one‐factor models and marginal maximum likelihood estimation. British Journal of Mathematical and Statistical Psychology. 62(1). 57–77. 24 indexed citations

17.

Neale, Michael C., Gitta H. Lubke, Steven H. Aggen, & Conor V. Dolan. (2005). Problems With Using Sum Scores for Estimating Variance Components: Contamination and Measurement Noninvariance. Twin Research and Human Genetics. 8(6). 553–568. 27 indexed citations

18.

Neale, Michael C., Gitta H. Lubke, Steven H. Aggen, & Conor V. Dolan. (2005). Problems With Using Sum Scores for Estimating Variance Components: Contamination and Measurement Noninvariance. Twin Research and Human Genetics. 8(6). 553–568. 31 indexed citations

19.

Lubke, Gitta H., Conor V. Dolan, & Michael C. Neale. (2004). Implications of Absence of Measurement Invariance for Detecting Sex Limitation and Genotype by Environment Interaction. Twin Research. 7(3). 292–298. 22 indexed citations

20.

Boomsma, Dorret I., et al.. (1997). Genetic longitudinal analysis of anxiety, neuroticism and depressions in adolescent and young-adult Dutch twins. Behavior Genetics. 27. 1 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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