Advances in Psychological Research Methods - APS300487
Title: Advances in Psychological Research Methods
Guaranteed by: Department of Psychology (21-KPS)
Faculty: Faculty of Arts
Actual: from 2024
Semester: summer
Points: 3
E-Credits: 4
Examination process: summer s.:
Hours per week, examination: summer s.:1/1, C [HT]
Capacity: 30 / unknown (10)
Min. number of students: unlimited
4EU+: no
Virtual mobility / capacity: no
Key competences:  
State of the course: taught
Language: English
Teaching methods: full-time
Level:  
Additional information: https://dl1.cuni.cz/course/view.php?id=17393
Note: course can be enrolled in outside the study plan
enabled for web enrollment
priority enrollment if the course is part of the study plan
Guarantor: Martin Danka, M.Sc.
Teacher(s): Mgr. Markéta Čihařová, M.Sc.
Martin Danka, M.Sc.
Bc. Jiří Štipl
Incompatibility : APS300487E
Is incompatible with: APS300487E
SS schedule   Noticeboard   
Annotation -
This module provides an accessible introduction to modern research methods, focusing on widely applicable approaches that are shaping research practices internationally but remain underutilised in Czech psychology. It covers current trends in various research designs and psychometrics, including statistical techniques that are less commonly taught in other modules. The module emphasises understanding concepts, building intuition, and applying these methods, rather than focusing on formal theory. The teaching is split into three main blocks, each centred on different research designs. Block 1 covers advanced experimental designs, modern systematic reviews and meta-analyses. Block 2 focuses on studying causal relationships using non-experimental designs. Block 3 focuses on current approaches to analysing latent data structures and interpreting scale scores. To keep the module accessible, each block starts with a brief refresher on traditional methods before progressing to more advanced topics.<br>
Last update: Danka Martin, M.Sc. (13.01.2025)
Aim of the course -

Aim:
This module aims to introduce emerging perspectives and new methods in psychological research, focusing on conceptual understanding and practical applications in modern psychological studies.

Knowledge:
By the end of this module, students will understand the fundamental principles of experimental, observational, and meta-analytic research designs, as well as the analysis of psychological scales. They can describe the limitations of standard methods and appreciate the advantages and underlying assumptions of more advanced alternatives.

Skills:
By the end of this module, students will be able to apply the research methods covered to their own projects, interpret the results of studies that use these methods, and critically evaluate their strengths and limitations.

Last update: Danka Martin, M.Sc. (13.01.2025)
Course completion requirements -

Assessment:

  1. Practical assignment: Students will choose and complete an independent practical assignment. Three assignments are available, each corresponding to the methods covered in the three module blocks. Students are required to complete only one of these assignments.

  2. Attendance: The module consists of eight lectures. Students should attend at least five, with attendance counted only if they are present for at least half of the lecture. Those who attend only three or four lectures can complete an additional practical assignment to make up for the missed sessions. Thus, while attending at least three lectures is mandatory, students attending fewer than five must do extra work.

  3. Open-book quizzes: After each block or lecture, students will independently complete a practice quiz. These quizzes are designed to help reinforce the material, so the results do not count towards passing the module. The only requirement is that they are completed and submitted. Students are free to use their own materials, such as notes, textbooks, and slides, when completing the quizzes.

Last update: Danka Martin, M.Sc. (13.01.2025)
Literature -

Key Reading:

Block 1: Experimental Studies, Systematic Reviews and Meta-Analyses

Cuijpers, P. (2016). Meta-analyses in mental health research. A practical guide. Vrije Universiteit. https://research.vu.nl/en/publications/meta-analyses-in-mental-health-research-a-practical-guide

Karyotaki, E., Klein, A. M., Ciharova, M., Bolinski, F., Krijnen, L., De Koning, L., De Wit, L., Van Der Heijde, C. M., Ebert, D. D., Riper, H., Batelaan, N., Vonk, P., Auerbach, R. P., Kessler, R. C., Bruffaerts, R., Struijs, S., Wiers, R. W., & Cuijpers, P. (2022). Guided internet-based transdiagnostic individually tailored Cognitive Behavioral Therapy for symptoms of depression and/or anxiety in college students: A randomized controlled trial. Behaviour Research and Therapy, 150, 104028. https://doi.org/10.1016/j.brat.2021.104028

Block 2: Causal Inference in Observational Studies

Hernán, M. A. (2018). The C-word: Scientific euphemisms do not improve causal inference from observational data. American Journal of Public Health, 108(5), 616-619. https://doi.org/10.2105/AJPH.2018.304337

Block 3: Sum Scores as a Central Concept in Psychometrics

Sijtsma, K., Ellis, J. L., & Borsboom, D. (2024). Recognize the Value of the Sum Score, Psychometrics’ Greatest Accomplishment. Psychometrika, 89(1), 84-117. https://doi.org/10.1007/s11336-024-09964-7


Recommended: 

Block 1: Experimental Studies, Systematic Reviews and Meta-Analyses

Everitt, B. S., & Wessely, S. (2008). Clinical trials in psychiatry (2nd ed). J. Wiley & Sons.

Harrer, M., Cuijpers, P., Furukawa, T. A., & Ebert, D. D. (2022). Doing meta-analysis with R: A hands-on guide. CRC Press. https://bookdown.org/MathiasHarrer/Doing_Meta_Analysis_in_R/

Miguel, C., Karyotaki, E., Ciharova, M., Cristea, I. A., Penninx, B. W. J. H., & Cuijpers, P. (2023). Psychotherapy for comorbid depression and somatic disorders: A systematic review and meta-analysis. Psychological Medicine, 53(6), 2503-2513. https://doi.org/10.1017/S0033291721004414

Block 2: Causal Inference in Observational Studies

Barrett, M., D’Agostino McGowan, L., & Gerke, T. (2024). Causal Inference in R [Work in progress]. https://www.r-causal.org/

Hernán, M., & Robins, J. (2020). Causal Inference: What If. Chapman & Hall/CRC. https://miguelhernan.org/whatifbook

Poppe, L., Steen, J., Loh, W. W., Crombez, G., De Block, F., Jacobs, N., Tennant, P. W. G., Cauwenberg, J. V., & Paepe, A. L. D. (2024). How to develop causal directed acyclic graphs for observational health research: A scoping review. Health Psychology Review, 1-21.https://doi.org/10.1080/17437199.2024.2402809

Block 3: Sum Scores as a Central Concept in Psychometrics

Epskamp, S., Borsboom, D., & Fried, E. I. (2018). Estimating psychological networks and their accuracy: A tutorial paper. Behavior Research Methods, 50(1), 195-212. https://doi.org/10.3758/S13428-017-0862-1/FIGURES/9

Revelle, W., & Condon, D. M. (2019). Reliability from α to ω: A tutorial. Psychological Assessment, 31(12). https://doi.org/10.1037/pas0000754

Gary, S., Lenhard, W., Lenhard, A., & Robitzsch, A. (2021). Modelling Norm Scores with the cNORM Package in R. Psych 2021, Vol. 3, Pages 501-521, 3(3), 501-521. https://doi.org/10.3390/PSYCH3030033

Last update: Danka Martin, M.Sc. (23.01.2025)
Syllabus -

Block 1: Experimental Studies, Systematic Reviews and Meta-Analyses

Part 1: Experimental studies

  • Refresher: randomisation, between-subjects and within-subjects designs, sources of bias

  • Intention-to-treat and per-protocol effects

  • Advanced randomisation techniques

  • Advanced experimental designs (e.g., MOST, adaptive and sequential designs)

  • Reporting standards

  • Missing data (mechanisms of missingness, complete-case analysis, methods assuming missing at random)

Part 2: Systematic Reviews and Meta-Analyses

  • A step-by-step guide to systematic reviews, reporting standards (PRISMA)

  • Standard approaches to meta-analysis

  • Publication bias (how to assess and address publication bias)

  • New approaches (multilevel, network, and individual participant data meta-analysis)

Block 2: Causal Inference for Observational Studies

  • Refresher: correlation vs causation, the third variable problem, observational designs (cross-sectional, longitudinal, and case-control studies)

  • Reporting standards (STROBE)

  • Challenging the taboo: causation in observational studies

  • Defining causal effects using the potential outcomes framework

  • Assumptions for identifying and estimating causal effects

  • Using causal diagrams to understand relationships: confounders, colliders, mediators, effect modifiers, and interactions between causes

  • Causal analysis of observational studies

    • Methods invoking the “no unmeasured confounding“ (NUC) assumption

    • Methods replacing NUC with other assumptions (e.g., instrumental variables and natural experiments)

Block 3: Sum Scores as the Central Concept in Psychometrics

Part 1: From Items to Sum Scores

  • Refresher: Measurement in psychology, measurement error, scales and latent structures, common and partial correlations.

  • A review or introduction to basic psychometric methods, focusing on the role of sum scores:

    • Classical Test Theory (CTT)

    • Exploratory and Confirmatory Factor Analysis (EFA/CFA)

    • Item Response Theory (IRT)

    • Network psychometrics.

Part 2: From Sum Scores to Percentiles

  • Quantiles and standard scores.

  • Practical issues in norming: ceiling and floor effects, granularity of scores, “continuity correction”, indistinguishable percentile levels.

  • Age-based norming

    • Basic approaches

    • Simple regression norms and advanced approaches using GAMLSS

    • IRT for continuous norming.

Last update: Danka Martin, M.Sc. (13.01.2025)
Entry requirements -

Entry requirements: This module is open to all students interested in recent developments in psychological research methods. It assumes a basic understanding of statistics, research methods, and psychometrics, as typically covered in undergraduate psychology modules. However, students are not required to have formally completed any specific prior modules, as each block will begin with a refresher on essential concepts.

Last update: Dragomirecká Eva, PhDr., Ph.D. (29.10.2024)