Visualising and modelling changes in categorical variables in longitudinal studies.

ABSTRACT:

Background

Graphical techniques can provide visually compelling insights into complex data patterns. In this paper we present a type of lasagne plot showing changes in categorical variables for participants measured at regular intervals over time and propose statistical models to estimate distributions of marginal and transitional probabilities.

Methods

The plot uses stacked bars to show the distribution of categorical variables at each time interval, with different colours to depict different categories and changes in colours showing trajectories of participants over time. The models are based on nominal logistic regression which is appropriate for both ordinal and nominal categorical variables. To illustrate the plots and models we analyse data on smoking status, body mass

SUBMITTER: Jones M 

PROVIDER: S-EPMC3938907 | biostudies-literature | 2014 Feb

REPOSITORIES: biostudies-literature