Advanced Methods in Research Synthesis

Code:

M100

Acronym:

MASL

Keywords
Classification	Keyword
OFICIAL	Methods

Instance: 2023/2024 - 1S

Active?	Yes
Responsible unit:	Psychology
Course/CS Responsible:	Master Degree in Psychology

Cycles of Study/Courses

Acronym	No. of Students	Study Plan	Curricular Years	Credits UCN	Credits ECTS	Contact hours	Total Time
MPSIC	148	Plano Oficial do ano letivo 2021	1	-	3	27	81

Teaching language

Portuguese

Objectives

Introduction to methods for the systematic review/synthesis of the scientific literature, including procedures for meta-analysis.

Learning outcomes and competences

At the end of this course, student should:

1. Know the different typologies of literature syntheses (e.g., systematic/ non-systematic, narrative/quantitative) and the advantages of systematic reviews and meta-analyses.
2. Be able to appreciate the strength of empirical evidence as a function of study quality and research design, and to frame research syntheses as summaries of accumulated evidence.
3. Know and be able to apply the steps involved in systematic reserach synthesis, from the formulation of the research problem to the writing of the synthesis itself.
4. Understand and apply the statistical procedures for calculating effect sizes, combining them meta-analytically, and to analyse effect size heterogeneity across studies.
5. Know computation tools (software) that allow conducting systematic research syntheses and meta-analyses.

Working method

Presencial

Program

1. Research Synthesis
1.1. From narrative literaure reviews to the systematic synthesis of research results
1.2. Brief history of research synthesis and meta-analysis
1.3. The “reproducibility crysis”: consequences for systematic reviews

2. Systematic research synthesis
2.1. Formulating the problem
2.2. Search for studies
2.3. Study selection (inclusion/exclusion criteria)
2.4. Coding of study characteristics
2.5. Assessment of the quality of evidence
2.6. Presentation and interpretaion of results

3. Statistical analysis and effect size measures

4. Meta-analysis: combining effect sizes
4.1. Methods for combining effect sizes (meta-analysis)
4.2. Analysis of publication bias
4.3. Heterogeneity analysis
4.3. Presentation of meta-analytic results

5. Practical issues
5.1. Software for conducting systematic research syntheses and meta-analyses
5.2. Tools supporting reproducibility (from pre-registration to publication)

Mandatory literature

Harris Cooper; Research synthesis and meta-analysis. ISBN: 978-1-4833-3115-7
Geoff Cumming; Introduction to the new statistics. ISBN: 978-1-138-82552-9

Complementary Bibliography

Jacob Cohen; Statistical power analysis for the behavioral sciences. ISBN: 0-8058-0283-5
Siddaway, A. P., Wood, A. M., & Hedges, L. V. ; How to do a systematic review: A best practice guide for conducting and reporting narrative reviews, meta-analyses, and meta-syntheses. Annual Review of Psychology, 70, 747–770, 2019 (https://doi.org/10.1146/annurev-psych-010418-102803)
Harris Cooper; The handbook of research synthesis and meta-analysis. ISBN: 978-0-87154-005-8

Teaching methods and learning activities

Pedagogical models:
- Plenary lectures;
- Broad student participation in lectrures (classroom response system, e.g., https://clicker.up.pt/, wooclap);
- Weekly exercises to consolidate and develop class contents (in the Moodle platform) and operationalize the practical application of all steps involved in research synthesis and meta-analysis;
- Online forum for answering student questions (Moodle).

Software

JASP Team (2023). JASP (Version 0.17) [Computer software]. Retrieved from https://jasp-stats.org/
https://rayyan.ai [Ouzzani, M., Hammady, H., Fedorowicz, Z., & Elmagarmid, A. (2016) Rayyan - a web and mobile app for systematic reviews. Systematic Reviews, 5, 210. https://doi.org/10.1186/s13643-016-0384-4]

Evaluation Type

Distributed evaluation with final exam

Assessment Components

designation	Weight (%)
Exame	70,00
Trabalho laboratorial	30,00
Total:	100,00

Amount of time allocated to each course unit

designation	Time (hours)
Estudo autónomo	40,00
Frequência das aulas	27,00
Trabalho laboratorial	14,00
Total:	81,00

Eligibility for exams

A student will be approved if her final classification is equal to or greater than 9.5 points (out of 20) and she has obtained a score of at least 8 points in each of the evaluation components.

Calculation formula of final grade

Distributed evaluation with final exam:
- Weekly exercises: 30% of the final grade
- Final exam: 70% of the final grade

The score of the Weekly exercises (0-20 points) will be the mean of the scores obtained in all weeks except the week in which the student obtained the lowest score.

Special assessment (TE, DA, ...)

Students under special regulations (e.g., working students) may complete the course via a final exam, but must contact the teacher at the beginning of the semester to request this evaluation format.

Classification improvement

Classification improvement of the theoretical component (exam) may be done in the terms specified by the current regulations.