MSc Data Science (Social Analytics) / Course details

Year of entry: 2024

Course unit details:
Complex Survey Designs and Analysis

Course unit fact file
Unit code SOST70032
Credit rating 15
Unit level FHEQ level 7 – master's degree or fourth year of an integrated master's degree
Teaching period(s) Semester 2
Available as a free choice unit? Yes

Overview

This course provides an insight into the design and methodological issues for the analysis of complex surveys. It also introduces analytical methods and software for handling complex datasets. 

Pre/co-requisites

Unit title Unit code Requirement type Description
Introduction to Statistical Modelling SOST70011 Pre-Requisite Recommended

The students should have some familiarity with survey research and statistical modelling. A pre-requisite of the course is: Introduction to Statistical Modelling (ISM - SOST70011).

Aims

This course provides an insight into the design and methodological issues for the analysis of complex surveys. It also introduces analytical methods and software for handling complex survey datasets.

Learning outcomes

At the end of this module, students should be able to:

• Understand methodological concepts in survey design, estimation and adjusting for nonresponse.

• Assess the strengths and weaknesses of complex survey designs and the resulting secondary survey data.

• Assess how aspects of survey design will impact on the analysis.

• Understand and apply multilevel and longitudinal models with complex survey data.

• Use STATA (and other) software to analyse complex survey data.

• Understand the difference between model-based and design-based approaches to handling complex survey designs.

Teaching and learning methods

A combination of lecture, tutorials and computer clusters (average 3 hour per week online and on campus)

Assessment methods

Method Weight
Other 15%
Written assignment (inc essay) 85%

The assessment for this module will be based on three mini quizzes worth 5% each (15%) and one piece of coursework of 3,000 words (85%).

Feedback methods

There are various opportunities for providing formative feedback on students' work and questions, for example with BB discussion boards and at tutorials. There are also two integrated formative tasks:

• A modelling exercise with a given dataset (due before Easter break): students are invited to run and present the results of a (multilevel) model with their interpretation via Turnitin. Feedback is provided at individual level and also combined common misunderstandings are shared to resolve confusions and enhance understanding.

• A student presentation of their proposed complex survey design study (Part A of the final assignment) - to get live feedback from teaching team and peers (Week 11 or 12).

Recommended reading

• Blair, J., Czaja, R. and Blair, E. (2014) Designing Surveys: A Guide to Decisions and

procedures, 3rd edition. CA: Sage Publication.

• Heeringa, S. G., West, B. T, & Berglund, P. A. (2010). Applied Survey Data Analysis. Boca Raton: CRC Press.

• Lehtonen, R. and Pahkinen, E.J. (2004) Practical Methods for Design and Analysis of Complex Surveys, 2nd edition. Chichester: John Wiley & Sons.

• Lohr, S.L. (2009) Sampling: Design and Analysis, 2nd edition. Boston: Brooks/Cole.

• Snijders, T.A.B. & Bosker, R.J. (2012) Multilevel analysis: An Introduction to Basic and Advanced Multilevel Modelling, 2nd edition. London: Sage.

Study hours

Scheduled activity hours
Lectures 36
Independent study hours
Independent study 114

Teaching staff

Staff member Role
Maria Pampaka Unit coordinator

Additional notes

Information

Compulsory for SRMS

Part time students must take ISM prior to CSDA

Return to course details