Investigate change in time using R
27/04/2023 - 28/04/2023
The University of Manchester
Dr Alexandru Cernat
Intermediate (some prior knowledge)
Claire Spencer, 0161 275 4579, firstname.lastname@example.org
Longitudinal data (data collected multiple times from the same cases) is becoming increasingly popular due to the important insights it can bring us. For example, it can be used to track how individuals change in time and what are the causes of change, it can also be used to understand causal relationships or used as part of impact evaluation. Unfortunately, traditional models such as OLS regression are not appropriate as multiple observations are nested within each individual. In order to leverage the longitudinal aspect of the data and to get correct estimates more specialised statistical models are needed.
Structural Equation Modelling (SEM) and MultiLevel Modelling (MLM) are two frameworks that can be used to analyse longitudinal data. They offer a series of advantages compared to other approaches such as: separating within and between variation, the inclusion of multiple relationships (path analysis, mediation, etc.), the correction for measurement error, multi-group analysis, etc.
The course will cover some of the basics and more advanced Multilevel Models for Change and Latent Growth Models using the lme4 and lavaan packages in R. In addition to the fact that the packages are free and open source they also offer great flexibility, being able to estimate many of the models typically used in with longitudinal data.
The course covers:
• Introduction to lme4 and lavaan packages;
• Short discussion of the multilevel framework;
• Short discussion of the SEM framework;
• Multilevel Model for Change;
• Latent Growth Models;
The course will be a combination of lecturing and practicals using real world data. The exercises and practicals will be shared with the students on the day of the lecture.
Cernat, A. (2023). Longitudinal Data Analysis Using R. Leanpub
You can find out more about the teacher at: http://www.alexcernat.com
To prepare before class
All the exercises will be in R. Please install the latest version of R (https://cran.r-project.org/) and latest version of Rstudio (https://posit.co/download/rstudio-desktop/) before the class. Also install in advance the lavaan (run in R: install.packages("lavaan", dep =TRUE)), lme4 (run in R: install.packages("lme4", dep =TRUE)) and the tidyverse (run in R: install.packages("tidyverse", dep =TRUE)) packages.
The fee per teaching day is: • £30 per day for students • £60 per day for staff working for academic institutions, Research Councils and other recognised research institutions, registered charity organisations and the public sector • £100 per day for all other participants If it is no longer possible to run a course due to circumstances beyond its control, NCRM reserves the right to cancel the course at its sole discretion at any time prior to the event. In this event every effort will be made to reschedule the course. If this is not possible or the new date is inconvenient a full refund of the course fee will be given. NCRM shall not be liable for any costs, losses or expenses that may be incurred as a result of the cancellation of a course. The University of Southampton’s Online Store T&Cs also continue to apply.
Website and registration:
Quantitative Data Handling and Data Analysis, Multilevel Modelling , Longitudinal Data Analysis, Quantitative Software
Related publications and presentations:
Quantitative Data Handling and Data Analysis
Longitudinal Data Analysis