SC968-7-SP-CO:
Advanced Quantitative Analysis: Models for Cause and Effect
2020/21
Sociology and Criminology
Colchester Campus
Spring
Postgraduate: Level 7
Current
Sunday 17 January 2021
Friday 26 March 2021
20
29 June 2020
Requisites for this module
(none)
(none)
(none)
(none)
(none)
MSC B99012 Health Research,
MSC L31012 Survey Methods for Social Research,
MSC L310MO Survey Methods for Social Research,
MSC L31112 Migration Studies,
MSC L31124 Migration Studies,
MPHDB79748 Health Studies,
PHD B79748 Health Studies
Each lecture is followed by a 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.
The data used will a subset of the British Household Panel Survey, and the exercises will involve the sort of analysis that professional social scientists might need to undertake.
Most sessions will build on the work of a previous session; it is therefore important that students keep copies of all their do-files and outputs.
Students should already be familiar with the fundamentals of Stata, including:
* basic data management techniques
* working in interactively and with do-files
* basic analytical techniques such as OLS, logit and probit
If you are unsure about your competence in Stata, please talk to the course tutors well before the start of the course. All students are strongly encouraged to attend an Understanding Society training course, normally held in the autumn, to prepare for the lab sessions.
This course gives students a practical grounding in the theory and methods of panel data analysis.
It has the following key aims:
1. To allow students to interpret and critically assess published studies using panel data
2. To provide students with the skills and confidence to manipulate panel datasets on their own in the future
3. To give an overview of different approaches to panel data analysis
4. To develop practical skills in selecting and conducting different types of panel data analysis
5. To provide an opportunity for students to compare results of analysing the same data with different panel methods
6. The course includes a review of standard regression methods (OLS, logit and probit) and covers longitudinal data manipulation, transition matrices, continuous and discrete fixed and random effects models, and survival analysis.
Please note that assessment information is currently showing for 2019-20 and will be updated in September.
Lecture Outline
Week 16
A review of concepts for regression modeling, or what you should know already
Week 17
Understanding and using panel data: introduction and management
Week 18
Understanding and using panel data: merging files and weights
Week 19
Panel data methods I: transition matrices, lagged and first difference models
Week 20
Panel data methods II: Fixed effects and random effects models
Week 21
Reading week: readin and evaluating published panel data studies
Week 22
Fixed and random effects models - properties, tests and specification issues
Week 23
Panel data methods III: Event history analysis
Week 24
Event history analysis - properties, tests and specification issues
Week 30
Review and sum up
Week 31
In Class Test
Lab Sessions
Each lecture is followed by a 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 several hours in the lab each week, in addition to these scheduled sessions, in order to cover the work.
The data used will be a subset from the British Household Panel Survey (BHPS), and the exercises will involve the sort of analysis that professional social scientists might need to undertake.
Most sessions will build on the work of a previous session; it is therefore important that students keep copies of all their do-files and outputs.
Students should already be familiar with the fundamentals of Stata, including:
* basic data management techniques
* working in interactive and batch mode
* basic analytical techniques such as OLS, logit and probit
If you are unsure about your competence in Stata, please talk to the course tutors well before the start of the course.
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 any essential texts. To see non-essential items, please refer to the module's reading list.
Assessment items, weightings and deadlines
| Coursework / exam |
Description |
Deadline |
Coursework weighting |
| Coursework |
applied coursework |
|
50% |
| Coursework |
Take home Test. |
|
50% |
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.
Overall assessment
Reassessment
Module supervisor and teaching staff
Dr Cara Booker, email: cbooker@essex.ac.uk.
Dr Cara Booker
Michele Hall, Graduate Administrator, Telephone 01206 873051, Email: socpgadm@essex.ac.uk
Yes
No
No
Prof Paul Stretesky
The University of Northumbria at Newcastle
Professor of Criminology
Prof Benjamin Bradford
University College London
Professor
Available via Moodle
Of 605 hours, 0 (0%) hours available to students:
605 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).
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