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Cathie Marsh Institute for Social Research

Introduction to Longitudinal Data Analysis

Date: 12 April 2018
Duration: 1 day (9.45am-4.30pm)
Instructor: Ian Plewis
Level:
 Introductory
Course Fee: £195 (£140 for those from educational, government and charitable institutions).

CMI offers up to five subsidised places at a reduced rate of £60 per course day to research staff and students within Humanities at The University of Manchester. These places are awarded in order of application. In some instances, such as for unfunded PhD students, we may be able to offer free or bursary places.

Please note: this is not guaranteed and is considered on a case by case basis. Please contact us for more information.

Outline

The course covers basic concepts in longitudinal design and analysis.

The morning session focuses on the strengths and methodological difficulties of the longitudinal approach such as defining longitudinal populations and target samples; levels and dimensions of change; age, period and cohort effects. There will be one small group discussion.

After lunch, we start with an overview session on the sources and causes of missing data (attrition, etc.), and how to adjust for missingness; this will be followed by another group exercise.

Objectives

By the end of the course, students should have gained:

  • an understanding of the different ways of measuring and explaining change using longitudinal data;
  • an appreciation of the particular problems posed by missing data in longitudinal research;
  • a basic understanding of ways of adjusting for missing data and
  • confidence to address questions about longitudinal design and missing data.

Prerequisites

Students should have some background in empirical social science and a basic grounding in statistical modelling, at least in linear regression.

Recommended reading

  • Firebaugh, G. (1997) Analyzing Repeated Surveys. Thousand Oaks, Ca.: Sage.
  • Lynn, P. (ed.) (2009) Methodology of Longitudinal Studies. Chichester: Wiley.

About the instructor

Ian Plewis is Emeritus Professor of Social Statistics at The University of Manchester with a wealth of practical experience and theoretical knowledge of designing longitudinal studies and using longitudinal data. 

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