Publications

Bailey, N. A., Golino, H. F., & Allen, J. P. (2026). Autonomy and relatedness in mother-adolescent interactions: An investigation using Exploratory Graph Analysis. Family Process, 65(1), e70116. https://doi.org/10.1111/famp.70116

Christensen, A. P., & Choi, J. (2026). Network accuracy across local, mesoscale, and global structures using Stochastic Block Models. PsyArXiv. https://doi.org/10.31234/osf.io/9d4nm_v2

Garrido, L. E., Russell-Lasalandra, L. L., & Golino, H. (2026). Estimating dimensional structure in generative psychometrics: Comparing PCA and network methods using large language model item embeddings. PsyArXiv. https://doi.org/10.31234/osf.io/2s7pw_v1

Golino, H. (2026). Optimizing the landscape of LLM embeddings with Dynamic Exploratory Graph Analysis for generative psychometrics: A Monte Carlo study. arXiv. https://arxiv.org/abs/2601.17010

Graña, D. F., Kreitchmann, R. S., Sorrel, M. A., Garrido, L. E., & Abad, F. J. (2026). Dimensionality assessment in forced-choice questionnaires: First steps toward an exploratory framework. Educational and Psychological Measurement, 86(1), 54–81. https://doi.org/10.1177/00131644251358226

Pereira, R. B., Manfro, P. H., Viduani, A., Cosenza, V., Buchweitz, C., Piccin, J., et al. (2026). What retrospective and dynamic assessments tell us about youth depression: A network analysis perspective. Journal of Affective Disorders, 399, 121099. https://doi.org/10.1016/j.jad.2025.121099

Tomašević, A., Golino, H., & Christensen, A. P. (2026). transforEmotion: An open-source R package for emotion analysis using transformer-based generative AI models. Computational Communication Research, 8(2), 1–40. https://doi.org/10.5117/CCR2026.2.2.TOMA

Abitante, G., Griffith, J. M., Christensen, A. P., Cole, D., Young, J. F., & Hankin, B. L. (2025). Developmental changes in youth affect: A within-person approach. Emotion. https://doi.org/10.1037/emo0001591

Christensen, A. P., Golino, H., Abad, F. J., & Garrido, L. E. (2025). Revised network loadings. Behavior Research Methods, 57(4), 114. https://doi.org/10.3758/s13428-025-02640-3

De Duro, E. S., Veltri, G. A., Golino, H., & Stella, M. (2025). Measuring and identifying factors of individuals' trust in Large Language Models. arXiv. https://arxiv.org/abs/2502.21028

Garrido, L. E., Christensen, A. P., Golino, H., Martínez-Molina, A., Arias, V. B., et al. (2025). A systematic evaluation of wording effects modeling under the exploratory structural equation modeling framework. Multivariate Behavioral Research, 60(6), 1169–1198. https://doi.org/10.1080/00273171.2025.2545362

Golino, H., Nesselroade, J., & Christensen, A. P. (2025). Toward a psychology of individuals: The ergodicity information index and a bottom-up approach for finding generalizations. Multivariate Behavioral Research, 60(3), 528–555. https://doi.org/10.1080/00273171.2025.2454901

Heshmati, S., Rombaoa, J. P., Merritt, S. H., & Christensen, A. P. (2025). Dynamic network models reveal personalized patterns of well-being in young adult daily lives. Scientific Reports. https://doi.org/10.1038/s41598-025-24897-6

Jiménez, M., Abad, F. J., Garcia-Garzon, E., Golino, H., & Christensen, A. P. (2025). Dimensionality assessment in bifactor structures with multiple general factors: A network psychometrics approach. Psychological Methods, 30(4), 770–792. https://doi.org/10.1037/met0000590

Kaiser, T., Herzog, P., Brakemeier, E. L., & Golino, H. (2025). Must we always go idiographic?: Information-theoretic approaches to testing structural ergodicity in temporal symptom networks. Cognitive Therapy and Research. https://doi.org/10.1007/s10608-025-10672-4

Krugel, C., & Christensen, A. P. (2025). Identifying psychometric problems using Exploratory Graph Analysis. PsyArXiv. https://doi.org/10.31234/osf.io/g57a2_v1

Samo, A., Garrido, L. E., Abad, F. J., Golino, H., McAbee, S. T., & Christensen, A. P. (2025). Revisiting the IPIP-NEO personality hierarchy with taxonomic graph analysis. European Journal of Personality. https://doi.org/10.1177/08902070251352590

Shi, D., Christensen, A. P., Day, E. A., Golino, H. F., & Garrido, L. E. (2025). Exploring estimation procedures for reducing dimensionality in psychological network modeling. Multivariate Behavioral Research, 60(2), 184–210. https://doi.org/10.1080/00273171.2024.2395941

Silvia, P. J., Rodriguez-Boerwinkle, R. M., Awa, K. N., Zabelina, D. L., & Christensen, A. P., et al. (2025). Evaluating the structure of the Aesthetic Responsiveness Assessment (AReA) with Bootstrap Exploratory Graph Analysis. Empirical Studies of the Arts, 43(1), 550–564. https://doi.org/10.1177/02762374241259935

Briganti, G., Scutari, M., Epskamp, S., Borsboom, D., Hoekstra, R. H. A., Golino, H. F., & Christensen, A. P. (2024). Network analysis: An overview for mental health research. International Journal of Methods in Psychiatric Research, 33(4), e2034. https://doi.org/10.1002/mpr.2034

Christensen, A. P. (2024). Unidimensional community detection: A Monte Carlo simulation, grid search, and comparison. Psychological Methods. https://doi.org/10.1037/met0000692

Christensen, A. P., Garrido, L. E., Guerra-Peña, K., & Golino, H. (2024). Comparing community detection algorithms in psychometric networks: A Monte Carlo simulation. Behavior Research Methods, 56(3), 1485–1505. https://doi.org/10.3758/s13428-023-02106-4

Christensen, A. P., & Golino, H. (2024). Exploratory Graph Model. PsyArXiv. https://doi.org/10.31234/osf.io/zkdr4

Garcia-Pardina, A., Abad, F. J., Christensen, A. P., Golino, H., & Garrido, L. E. (2024). Dimensionality assessment in the presence of wording effects: A network psychometric and factorial approach. Behavior Research Methods, 56(6), 6179–6197. https://doi.org/10.3758/s13428-024-02348-w

Golino, H., Jiménez, M., Garrido, L. E., & Christensen, A. P. (2024). Generalized Total Entropy Fit Index: A new fit index for dimensionality analysis of bifactor structures with multiple general factors in SEM and network psychometrics. PsyArXiv. https://doi.org/10.31234/osf.io/5g3hb

Jamison, L., Christensen, A. P., & Golino, H. F. (2024). Metric invariance in Exploratory Graph Analysis via permutation testing. Methodology, 20(2), 144–186. https://doi.org/10.5964/meth.12877

Jamison, L., Golino, H., & Christensen, A. P. (2024). Adjusted network loadings for Dynamic Exploratory Graph Analysis. PsyArXiv. https://doi.org/10.31234/osf.io/3hxra

Maertens, R., Götz, F. M., Golino, H. F., Roozenbeek, J., Schneider, C. R., Stanzel, A., et al. (2024). The Misinformation Susceptibility Test (MIST): A psychometrically validated measure of news veracity discernment. Behavior Research Methods, 56(3), 1863–1899. https://doi.org/10.3758/s13428-023-02124-2

Russell-Lasalandra, L. L., Christensen, A. P., & Golino, H. (2024). Generative psychometrics via AI-GENIE: Automatic item generation and validation via network-integrated evaluation. PsyArXiv. https://doi.org/10.31234/osf.io/fgbj4

Tomašević, A., Golino, H., & Christensen, A. P. (2024). Decoding emotion dynamics in videos using Dynamic Exploratory Graph Analysis and zero-shot image classification: A simulation and tutorial using the transforEmotion R package. PsyArXiv. https://doi.org/10.31234/osf.io/hf3g7

Brown, G. P., Delgadillo, J., & Golino, H. (2023). Distinguishing the dimensions of the original dysfunctional attitude scale in an archival clinical sample. Cognitive Therapy and Research, 47(1), 69–83. https://doi.org/10.1007/s10608-022-10333-w

Chen, Q., Christensen, A. P., Kenett, Y. N., Ren, Z., Condon, D. M., Bilder, R. M., & Qiu, J. (2023). Mapping the creative personality: A psychometric network analysis of highly creative artists and scientists. Creativity Research Journal, 35(3), 455–470. https://doi.org/10.1080/10400419.2023.2184558

Christensen, A. P., Cardillo, E. R., & Chatterjee, A. (2023). What kind of impacts can artwork have on viewers? Establishing a taxonomy for aesthetic impacts. British Journal of Psychology, 114(2), 335–351. https://doi.org/10.1111/bjop.12623

Christensen, A. P., Garrido, L. E., & Golino, H. (2023). Unique variable analysis: A network psychometrics method to detect local dependence. Multivariate Behavioral Research, 58(6), 1165–1182. https://doi.org/10.1080/00273171.2023.2194606

Kenett, Y. N., Cardillo, E. R., Christensen, A. P., & Chatterjee, A. (2023). Aesthetic emotions are affected by context: A psychometric network analysis. Scientific Reports, 13(1), 20985. https://doi.org/10.1038/s41598-023-48219-w

Merritt, S. H., & Christensen, A. P. (2023). An experimental study of dimension reduction methods on machine learning algorithms with applications to psychometrics. Advances in Artificial Intelligence and Machine Learning, 3(1), 760–777. https://www.oajaiml.com/uploads/archivepdf/86781149.pdf

Murri, M. B., Caruso, R., Christensen, A. P., Folesani, F., Nanni, M. G., & Grassi, L. (2023). The facets of psychopathology in patients with cancer: Cross-sectional and longitudinal network analyses. Journal of Psychosomatic Research, 165, 111139. https://doi.org/10.1016/j.jpsychores.2022.111139

Shi, D., Christensen, A. P., Day, E. A., Golino, H., & Garrido, L. E. (2023). A Bayesian approach for dimensionality assessment in psychological networks. PsyArXiv. https://doi.org/10.31234/osf.io/9rcev

Golino, H., Christensen, A. P., & Garrido, L. E. (2022). Exploratory graph analysis in context. Revista Psicologia: Teoria e Prática, 24(3), ePTPPA14197. https://doi.org/10.5935/1980-6906/ePTPIC15531.en

Golino, H., Christensen, A. P., Moulder, R., Kim, S., & Boker, S. M. (2022). Modeling latent topics in social media using Dynamic Exploratory Graph Analysis: The case of the right-wing and left-wing trolls in the 2016 US elections. Psychometrika, 87, 156–187. https://doi.org/10.1007/s11336-021-09820-y

Till, A. C., Florquin, R., Christensen, A. P., Golino, H., Kornreich, C., & Delhaye, M. (2022). Unique variable analysis of redundancy in ADHD items from the Conners Teacher Rating Scale-Revised: Short. Psychiatria Danubina, 34(Suppl 8), 214–219. https://hdl.handle.net/20.500.12907/43977

Christensen, A. P., Garrido, L. E., & Golino, H. (2021). What is bridge centrality? A comment on Jones, Ma, and McNally (2019). PsyArXiv. https://doi.org/10.31234/osf.io/a8svr

Christensen, A. P., & Golino, H. (2021). Estimating the stability of psychological dimensions via bootstrap exploratory graph analysis: A Monte Carlo simulation and tutorial. Psych, 3(3), 479–500. https://doi.org/10.3390/psych3030032

Christensen, A. P., & Golino, H. (2021). Factor or network model? Predictions from neural networks. Journal of Behavioral Data Science, 1(1), 85–126. https://doi.org/10.35566/jbds/v1n1/p5

Christensen, A. P., & Golino, H. (2021). On the equivalency of factor and network loadings. Behavior Research Methods, 53, 1563–1580. https://doi.org/10.3758/s13428-020-01500-6

Flores-Kanter, P. E., Garrido, L. E., Moretti, L. S., & Medrano, L. A. (2021). A modern network approach to revisiting the Positive and Negative Affective Schedule (PANAS) construct validity. Journal of Clinical Psychology, 77(10), 2370–2404. https://doi.org/10.1002/jclp.23191

Golino, H., Lillard, A. S., Becker, I., & Christensen, A. P. (2021). Investigating the structure of the Children's Concentration and Empathy Scale using Exploratory Graph Analysis. Psychological Test Adaptation and Development, 2(1), 35–49. https://doi.org/10.1027/2698-1866/a000008

Golino, H., Moulder, R., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., et al. (2021). Entropy fit indices: New fit measures for assessing the structure and dimensionality of multiple latent variables. Multivariate Behavioral Research, 56(6), 874–902. https://doi.org/10.1080/00273171.2020.1779642

Jamison, L., Christensen, A. P., & Golino, H. (2021). Optimizing Walktrap's community detection in networks using the Total Entropy Fit Index. PsyArXiv. https://doi.org/10.31234/osf.io/9pj2m

Christensen, A. P. (2020). Towards a network psychometrics approach to assessment: Simulations for redundancy, dimensionality, and loadings. Thesis Commons. https://doi.org/10.31234/osf.io/84kgd

Christensen, A. P., Golino, H., & Silvia, P. J. (2020). A psychometric network perspective on the validity and validation of personality trait questionnaires. European Journal of Personality, 34(6), 1095–1108. https://doi.org/10.1002/per.2265

Golino, H., Shi, D., Christensen, A. P., Garrido, L. E., Nieto, M. D., Sadana, R., et al. (2020). Investigating the performance of exploratory graph analysis and traditional techniques to identify the number of latent factors: A simulation and tutorial. Psychological Methods, 25(3), 292–320. https://doi.org/10.1037/met0000255

Golino, H., Thiyagarajan, J. A., Sadana, R., Teles, M., & Christensen, A. P., et al. (2020). Investigating the broad domains of intrinsic capacity, functional ability and environment: An exploratory graph analysis approach for improving analytical methodologies for healthy ageing research. PsyArXiv. https://doi.org/10.31234/osf.io/hj5mc

Rozgonjuk, D., Sindermann, C., Elhai, J. D., Christensen, A. P., & Montag, C. (2020). Associations between symptoms of problematic smartphone, Facebook, WhatsApp, and Instagram use: An item-level exploratory graph analysis perspective. Journal of Behavioral Addictions, 9(3), 686–697. https://doi.org/10.1556/2006.2020.00036

Christensen, A. P., Cotter, K. N., & Silvia, P. J. (2019). Reopening openness to experience: A network analysis of four openness to experience inventories. Journal of Personality Assessment, 101(6), 574–588. https://doi.org/10.1080/00223891.2018.1467428

Christensen, A. P., Gross, G. M., Golino, H. F., Silvia, P. J., & Kwapil, T. R. (2019). Exploratory graph analysis of the multidimensional schizotypy scale. Schizophrenia Research, 206, 43–51. https://doi.org/10.1016/j.schres.2018.12.018

Golino, H., & Christensen, A. P. (2019). EGAnet: Exploratory graph analysis — A framework for estimating the number of dimensions in multivariate data using network psychometrics [R package]. CRAN.

Kjellström, S., & Golino, H. (2019). Mining concepts of health responsibility using text mining and exploratory graph analysis. Scandinavian Journal of Occupational Therapy, 26(6), 395–410. https://doi.org/10.1080/11038128.2018.1455896

Christensen, A. P. (2018). NetworkToolbox: Methods and measures for brain, cognitive, and psychometric network analysis in R. The R Journal, 10(2), 422–439. https://doi.org/10.32614/RJ-2018-065

Christensen, A. P., Cotter, K. N., Silvia, P. J., & Benedek, M. (2018). Scale development via network analysis: A comprehensive and concise measure of openness to experience. PsyArXiv. https://doi.org/10.31234/osf.io/3raxt

Christensen, A. P., Kenett, Y. N., Aste, T., Silvia, P. J., & Kwapil, T. R. (2018). Network structure of the Wisconsin Schizotypy Scales–Short Forms: Examining psychometric network filtering approaches. Behavior Research Methods, 50(6), 2531–2550. https://doi.org/10.3758/s13428-018-1032-9

Golino, H. F., & Demetriou, A. (2017). Estimating the dimensionality of intelligence like data using exploratory graph analysis. Intelligence, 62, 54–70. https://doi.org/10.1016/j.intell.2017.02.007

Golino, H. F., & Epskamp, S. (2017). Exploratory graph analysis: A new approach for estimating the number of dimensions in psychological research. PLOS ONE, 12(6), e0174035. https://doi.org/10.1371/journal.pone.0174035