Experiments in Social Sciences: Online Experiments

Description:

This short course provides students with a state-of-the-art introduction to the intricacies and principles of experimental research in the social sciences. Participants will be guided through best practices for online experimental design and analysis, as well as learn how to carry out a range of Web-based experiments. 

The course will be structured with a blend of lectures and hands-on practical sessions, allowing students to actively engage and apply their learning.

The lectures introduce the experimental concepts and tools, while the computer practical involves hands-on exercises and analyses of the material taught in the lecture.

Pre-requisites:

• Familiarity with a basic understanding of introductory statistics, such as null hypothesis significance testing, confidence intervals, and linear regression.
• Working knowledge of processing and analysing data with R.
• R 3.3.0+
• RSTUDIO-2023.09.1-494

Event Outline:

Each day participants will have a 3-hour lecture in the morning between 10am and 1pm, followed by a 3-hour computer practical in the afternoon between 2pm and 5pm. There will be a 1-hour lunch break from 1pm until 2pm.

The course covers:

Day 1:

• Introduction to causal inference: the potential outcomes framework
• Randomisation: designs; assumptions; and violations 
• Treatment effects: ATE; ITT; CACE; and CATE
• Overview of online experiments: Vignette experiments; Conjoint experiments; Lab-in-the-field experiments; and interactive experiments

Day 2:

• Designing online experiments: priming; framing; conjoint; behavioural; and adaptive designs
• Measurement and data quality issues: manipulation checks
• Further external and internal validity issues: attention; satisficing; sampling; power analysis; and covariates 

Day 3:

• Reproducibility of online experiments: pre-registrations; code; data; and environment
• Ethics and deception
• Online data collection: using crowdsourcing platforms
• Analysis and treatment effect heterogeneity: parametric methods and causal forests method

By the end of this course, participants will:

• Have a comprehensive understanding of the potential and limitations of Web-based experiments.
• Be able to design and analyse different type of online experiments.
• Be able to critically evaluate and incorporate these designs in their own research pursuits.

Cost:

The fee per teaching day is £30 per day for registered students / £60 per day for staff at academic institutions, recognised research institutions and Research Council researchers, public sector staff and staff at registered charity organisations / £100 per day for all other participants In the event of cancellation by the delegate a full refund of the course fee is available up to two weeks prior to the course. No refunds are available after this date. If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course. The University of Southampton’s Online Store T&Cs also continue to apply.

Website and registration:

Register for this course

Region:

International

Keywords:

Experimental Research , Randomized Control Trials (RCT), Online experiments, Survey experiments, Social science experiments

Related publications and presentations from our eprints archive:

Experimental Research
Randomized Control Trials (RCT)

Back to the training database