RECSM Summer Methods School 2022

The RECSM Summer Methods School is a three-week intensive program covering diverse topics on survey methodology and advanced statistical analysis of survey data. Participants can create their own program choosing from 16 courses covering different topics.

All courses are taught by leading experts around the world. During the first week, we will offer five introductory courses including three on software programming in R, STATA & Phyton.

Target group: Professionals, Researchers, and Students, who wish to develop high-quality surveys and employ up-to-date statistical methods for survey data analysis. Potential attendees include survey practitioners, marketing professionals, social science students, and researchers.

Objective: To provide participants with the knowledge and skills needed to design surveys, implement statistical analysis and carry out quantitative research.

Format: On-site & Online

 

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CALENDAR

Week 1- Introductory courses

June 27 to July 1
Format: online & on-site

• STATA - Jordi Gumà
• R -Toni Rodon
• Python - Tom Paskhalis
• Quantitative methods in social research - Burak Sonmez
• Regression analysis - Daniele Toninelli  (*Preferred prerequisites: basic knowledge of statistics and a basic knowledge of Stata)

Week 2

July 4 to 8
Format: online & on-site

• Multilevel 1 (Introduction to multilevel models) - Carla Rampichini and Leonardo Grilli (*Prerequisites: Basic knowledge of statistical inference and linear regression. Knowledge of Stata is helpful but not necessary)
• Causal inference - Bruno Arpino (*Prerequisites: Familiarity with regression analysis and basic statistical concepts).
• Structural Equation Modeling - Terrence D. Jorgensen (*Prerequisites: R, fundamental statistical concepts, linear mode, basic psychometrics (classical test theory, reliability, and validity)
• Longitudinal Panel Models with Structural Equations - Terrence D. Jorgensen (*Prerequisites: R, fundamental statistical concepts, linear model (GLM) and its special cases: regression, t tests, ANOVA, and correlation. Familiarity with SEM).

Week 3

July 11 to 15
Format: online & on-site

• Big Data: Computational Analysis of Text - Carlos Arcila (*Prerequisites: Some bases in statistics is desirable).
• Machine Learning for Social Sciences - Christoph Kern (*Prerequisites: Solid knowledge of basic statistics, including linear and logistic regression. Familiarity with R is recommended)
• Experiments in Social Science: Survey experiments - Jordi Muñoz
• Probability sampling methods - Tarek Al-Baghal
• Questionnaire design - Diana Zavala-Rojas
• Multilevel 2 (Analyzing Comparative Longitudinal Survey Data Using Multilevel Models) - Malcolm Fairbrother (*Prerequisites: Basic understanding of multilevel models, and some experience of designing and fitting them).
• Social Networks - Luca De Benedictis (*Prerequisites: Basic knowledge of statistics. Previous use of R and R-Studio is strongly recommended).

Fees 

Introductory course

Duration: 8 hours/2 days

Students: 125€
Researchers: 230€
Professionals: 300€

Regular course

Duration: 12 hours/3 days

Students: 275€
Researchers: 450€
Professionals: 550€

Regular course

Duration: 8 hours/2 days

Students: 200€
Researchers: 300€
Professionals: 450€

*Registration opens March 14th, 2022

Discount

• 5% early bird discount to those who pay before May 16th, 2022
• 10% registering for at least 3 regular courses
• 20% registering for at least 5 regular courses 
• 25% UPF Members

 

Payment details

You can pay by bank transfer or with online payment.

The payment request with the payment details would be sent to the e-mail address you used in the online registration form.

​Cancellation Policy: All refund/cancellation requests must be provided via email to recsm@upf.edu and received prior to May 23, 2022. From May 24 cancellation will not be refunded.

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Organized by: RECSM