Introduction to Latent Growth Models using R (Online) (join a waiting list)
Date:
15/05/2020
Organised by:
The University of Manchester
Presenter:
Dr Alexandru Cernat
Level:
Entry (no or almost no prior knowledge)
Contact:
Claire Spencer, claire.spencer@manchester.ac.uk
Venue: Online
Description:
Longitudinal data (data collected multiple times from the same cases) is becoming increasingly popular due to the important insights it can bring us.
Structural Equation Modelling (SEM) offers a flexible framework in which longitudinal data can be analysed.
The course will be delivered online and cover some of the basics and more advanced Latent Growth Models using lavaan package in R.
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 individuals are nested in different time points. For this reason specialised statistical models need to be learned.
Structural Equation Modelling (SEM) offers a flexible framework in which longitudinal data can be analysed. It offers a series of advantages compared to other approaches such as traditional multilevel models: the inclusion of multiple relationships (path analysis, mediation, etc.), the inclusion of measurement error, the estimation of change in measurement error, multi-group analysis, etc.
The course will cover some of the basics and more advanced Latent Growth Models using the lavaan package in R. In addition to the fact that the package is free and open source it also offer great flexibility, being able to estimate most of the models typically used in Longitudinal SEM.
The course covers:
• Introduction to R and lavaan package;
• Short discussion of the SEM framework;
• 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 in the day of the lecture. the schedule is as follows:
09:50-10:00 Log on to Zoom
10:00-11:30 Introduction to lavaan and LGM
11:30-11:45 Comfort break
11:45-12:45 Hands on applications
12:45-13:45 Lunch break
13:45-15:15 Advanced LGM
15:15-15:30 Comfort break
15:30-17:00 Hands on applications
Pre course information
In advance you will receive a recommended reading list.
You can find out more about the teacher at: https://www.alexcernat.com
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://rstudio.com/products/rstudio/download/) before the class.
Also install in advance the lavaan (install.packages("lavaan", dep =TRUE)) and the tidyverse (install.packages("tidyverse", dep =TRUE)) packages.
The course will be delivered online via Zoom.
Cost:
The fee per teaching day is:
1. £30 - For UK registered postgraduate students
2. £60 - For staff at UK academic institutions, ESRC funded researchers and registered charity organisations
3. £100 - For all other participants
Website and registration:
Region:
North West
Keywords:
Longitudinal Data Analysis, Quantitative Software, R
Related publications and presentations:
Longitudinal Data Analysis
Quantitative Software
R