Julian Karch
Universitair docent
- Naam
- Dr. J.D. Karch
- Telefoon
- +31 71 527 3493
- j.d.karch@fsw.leidenuniv.nl
- ORCID iD
- 0000-0002-1625-2822
Julian Karch is universitair docent bij de sectie Methodologie & Statistiek van het Instituut Psychologie. Zijn voornaamste onderzoeksinteresses zijn de aanpassing en toepassing van statistische leermethodes om psychologische data te analyseren. Julian geeft les in statistiek in de master Methodology and Statistics in Psychology en de researchmaster Statistical Science.
Julian heeft een MSc Computer Science en is gespecialiseerd in statistical learning en data science. Hij heeft daarna een PhD in Quantitative Psychology gedaan aan het Max Planck Institute for Human Development in Berlijn. Tijdens zijn PhD was hij ook onderzoeker aan de Methodologie sectie van het Psychology Institute aan de Humboldt Universiteit te Berlijn. In 2016 verdedigde hij zijn proefschrift “A Machine Learning Perspective on Repeated Measures: Gaussian Process Panel and Person-Specific EEG Modeling”. Hierna bleef hij bij het Max Planck Instituut werken als postdoctorale onderzoeker. Tijdens zijn masterthesis en PhD werkte Julian ook bij de sectie Quantitative Psychology aan de Universiteit van Virginia en bij het Welcome Trust Centre for Neuroimaging van University College London.
Prijzen
- Best Research Proposal Award, MPS/UCL Symposium on Computational Psychiatry and Aging, 2016
Relevante links
Universitair docent
- Faculteit der Sociale Wetenschappen
- Instituut Psychologie
- Methodologie & Statistiek
- Ginkel J.R. van & Karch J.D. (2024), A comparison of different measures of the proportion of explained variance in multiply imputed data sets, British Journal of Mathematical and Statistical Psychology : .
- Karacaoglu M., Peerdeman K.J., Karch J.D., van Middendorp H. & Evers EW.M. (2024), Nocebo hyperalgesia and other expectancy-related factors in daily fibromyalgia pain: combining experimental and electronic diary methods, Journal of Psychosomatic Research 182: 111676.
- Carlier C., Karch J.D., Kuppens P. & Ceulemans E. (2024), A Comparison of measures for assessing profile similarity in Dyads, Psychologica Belgica 64(1): 72–84.
- Karch D.J., Perez-Alonso F. A. & Bergsma P.W. (2024), Beyond Pearson’s correlation: modern nonparametric independence tests for psychological research, Multivariate Behavioral Research 59(5): 957-977.
- Rahbari L. & Karch J.D. (2024), Dual nationality, anti‐citizenship, and xeno‐racism: online tropes on migrant (in)gratitude, and (in)adequate Britishness of Nazanin Zaghari‐Ratcliffe, The British Journal of Sociology : .
- Chen J., Bos E. van den, Karch J.D. & Westenberg P.M. (2023), Social anxiety is related to reduced face gaze during a naturalistic social interaction, Anxiety, Stress & Coping 36(4): 460-474.
- Pratiwi Bunga C., Dusseldorp E., Karch J.D. & de Rooij M. (2023), Predictive performance of psychological tests: is it better to use items than subscales?, Computational Statistics & Data Analysis 185: 107767.
- Blythe J.S., Peerdeman K.J., Veldhuijzen D.S. Karch, J.D. & Evers A.W.M. (2023), Electrophysiological markers for anticipatory processing of nocebo-augmented pain, PLoS ONE 18: e0288968.
- Baljé E. Astrid Karch D. Julian Greeven Anja Giezen van E. Anne Muste H. Eelco Arntz Arnoud Spinhoven Philip (2023), Avoidant Personality Disorder Severity Index: Dimensional structure and psychometric properties, Personality and Individual Differences : .
- Karch J.D. (2023), Outliers may not be automatically removed, Journal of Experimental Psychology: General 152(6): 1735–1753.
- Karch J.D. (2023), bmtest: a Jamovi module for Brunner–Munzel’s test: a robust alternative to Wilcoxon–Mann–Whitney’s test, Psych 5(2): 386-395.
- Kloos K., Meertens Q.A. & Karch J.D. (2022), UniLeiden at LeQua 2022: the first step in understanding the behaviour of the median sweep quantifier using continuous sweep, Working notes of the 2022 conference and labs of the evaluation forum (CLEF 2022), Bologna, Italy. CLEF 2022: Conference and Labs of the Evaluation Forum 5 september 2022 - 8 september 2022.
- De Rooij M.J., Karch J.D., Fokkema M., Bakk Z., Pratiwi B.C. & Kelderman H. (2022), SEM-based out-of-sample predictions, Structural Equation Modeling: A Multidisciplinary Journal : 1-17.
- Kloos K., Meertens Q., Scholtus S. & Karch J.D. (2021), Comparing correction methods to reduce misclassification bias. Baratchi M., Cao L., Kosters W.A, Lijffijt J., Rijn J.N. & Takes F.W. (red.), Artificial Intelligence and Machine Learning: 32nd Benelux Conference, BNAIC/Benelearn 2020, Leiden, The Netherlands, November 19–20, 2020, Revised Selected Papers. BNAIC/Benelearn 2020 19 november 2020 - 20 november 2020: Springer International Publishing AG. 64-90.
- Karch J.D. (2021), Psychologists should use Brunner-Munzel’s instead of Mann-Whitney’s U test as the default nonparametric procedure, Advances in Methods and Practices in Psychological Science 4(2): 1-14.
- Karch J.D., Brandmaier A.M. & Voelkle M.C. (2020), Gaussian process panel modeling—machine learning inspired analysis of longitudinal panel data, Frontiers in Psychology 11: 351.
- Karch J.D. (2020), Improving on adjusted R-squared, Collabra: Psychology 6(1): 45.
- Karch J.D., Fivelich E., Wenger E., Lisofski N., Becker M., Butler O., Martenson J., Lindenberger U.L., Brandmaier A.M. & Kühn S. (2019), Identifying predictors of within-person variance in MRI-based brain volume estimates, NeuroImage 200: 575-589.
- Karch JD (10 oktober 2016), A machine learning perspective on repeated measures: Gaussian process panel and person-specific EEG modeling (Dissertatie. Psychology, Lebenswissenschaftliche Fakulät, Humboldt Unversity of Berlin): Humboldt-Universität zu Berlin, Lebenswissenschaftliche Fakultät. Promotor(en): Brandmaier A. & Völkle M.
- Karch J.D., Sander M.C., Von Oertzen T., Brandmaier A.M. & Werkle-Bergner M. (2015), Using within-subject pattern classification to understand lifespan age differences in oscillatory mechanisms of working memory selection and maintenance, NeuroImage 118: 538-552.