Advanced Quantitative Analysis: Models for Cause and Effect
Postgraduate: Level 7
Monday 15 January 2024
Friday 22 March 2024
26 May 2023
Requisites for this module
MSC B99012 Health Research,
MSC L31012 Survey Methods for Social Research,
MSC L310MO Survey Methods for Social Research,
MSC L31112 Migration Studies,
MPHDB79748 Health Studies,
PHD B79748 Health Studies
This is an intensive module on advanced statistical modelling and casual techniques. The study materials will be covered over seven weeks. Each week, a one-hour lecture will be followed by a two-hour lab-based session, where students will use Stata to implement the methods covered in the lectures.
Due to the advanced research methods involved in this module, some prior experience of quantitative research methods is required. SC504-7-AU would be the most relevant module to take alongside this module.
The aims of this module are:
- To get familiar with the concept of causality in statistics
- To understand of the motivation and theoretical underpinnings of common counterfactual designs
- To gain an overview of common tools for causal analysis
- To understand the strengths and weaknesses of these tools for answering specific research questions
- To learn to use these tools in Stata
- To develop skills to critically discuss research findings and their interpretations in the scientific literature in terms of causality
By the end of this module, students will be expected to be able to:
- Use various methods for causal analysis
- Discuss the strengths, weaknesses, and limitations of different approaches
- Apply common tools for causality to specific research questions
- Implement counterfactual models in Stata
- Interpret outputs from counterfactual models in Stata
- Critically assess published studies from social science literature in terms of causality
The module will cover:
- Randomised Controlled Trials
- Conceptualising Causality
- Regression Designs
- Instrumental Variables
- Regression Discontinuity Designs
- Difference in Differences Models
Each one hour lecture is followed by a two hour lab-based session where students will use Stata to implement the methods covered in the lectures. Please note that this is an intensive course, and most students will need to spend one or two hours in the lab each week, in addition to these scheduled sessions, in order to cover the work.
This module does not appear to have a published bibliography for this year.
Assessment items, weightings and deadlines
|Coursework / exam
Exam format definitions
- Remote, open book: Your exam will take place remotely via an online learning platform. You may refer to any physical or electronic materials during the exam.
- In-person, open book: Your exam will take place on campus under invigilation. You may refer to any physical materials such as paper study notes or a textbook during the exam. Electronic devices may not be used in the exam.
- In-person, open book (restricted): The exam will take place on campus under invigilation. You may refer only to specific physical materials such as a named textbook during the exam. Permitted materials will be specified by your department. Electronic devices may not be used in the exam.
- In-person, closed book: The exam will take place on campus under invigilation. You may not refer to any physical materials or electronic devices during the exam. There may be times when a paper dictionary,
for example, may be permitted in an otherwise closed book exam. Any exceptions will be specified by your department.
Your department will provide further guidance before your exams.
Module supervisor and teaching staff
Dr Zsofia Boda, email: firstname.lastname@example.org.
Dr Zsofia Boda
Prof Benjamin Bradford
University College London
Available via Moodle
Of 15 hours, 15 (100%) hours available to students:
0 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s), module, or event type.
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