SC968-7-SP-CO:
Advanced Quantitative Analysis: Models for Cause and Effect

The details
2019/20
Sociology
Colchester Campus
Spring
Postgraduate: Level 7
Current
Monday 13 January 2020
Friday 20 March 2020
20
17 May 2019

 

Requisites for this module
(none)
(none)
(none)
(none)

 

(none)

Key module for

MSC B99012 Health Research,
MSC B990MO Health Research,
MSC L31012 Survey Methods for Social Research,
MSC L310MO Survey Methods for Social Research,
MSC L31112 Migration Studies

Module description

Introduction

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.

Module aims

This course gives students a practical grounding in the theory and methods of panel data analysis.

Module learning outcomes

It has the following key aims:

* To allow students to interpret and critically assess published studies using panel data

* To provide students with the skills and confidence to manipulate panel datasets on their own in the future

* To give an overview of different approaches to panel data analysis

* To develop practical skills in selecting and conducting different types of panel data analysis
* To provide an opportunity for students to compare results of analysing the same data with different panel methods
* 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.

Module information

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.

Learning and teaching methods

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.

Bibliography

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 Weighting
Coursework In-class Test 50%
Coursework applied coursework 20/03/2020 50%

Overall assessment

Coursework Exam
100% 0%

Reassessment

Coursework Exam
100% 0%
Module supervisor and teaching staff
Dr Ayse Guveli and Dr Silvia Avram (ISER)
Michele Hall, Graduate Administrator, Telephone 01206 873051, Email: socpgadm@essex.ac.uk

 

Availability
Yes
No
Yes

External examiner

Prof Paul Stretesky
The University of Northumbria at Newcastle
Professor of Criminology
Resources
Available via Moodle
Of 31 hours, 11 (35.5%) hours available to students:
20 hours not recorded due to service coverage or fault;
0 hours not recorded due to opt-out by lecturer(s).

 

Further information
Sociology

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