Longitudinal data is created when we take a number of measurements on each person (or other entity) at different points in time. To take these repeated measurements into account then methods like Mixed Effects Models and Generalized Estimating Equations are necessary.

In this workshop we will cover:

• The differences between independent, clustered, and longitudinal data

• A review of linear regression and Analysis of Variance

• Tukey tests (for identifying which groups are different)

• Levene’s test (for assessing whether the variance differs between groups)

• The Non-parametric equivalent forms for Analysis of Variance

• Mixed Effects models (fixed effects for the population means, and random effects for the variation between groups)

• Hierarchical and multi-level models

• Viewing longitudinal data as a form of multivariate data

• Different expressions for the correlation matrix for multivariate data

• Generalised Estimating Equations

• Likelihood ratio test (for comparing different correlation structures)

• The problem with missing data in longitudinal studies

• Data Missing Completely At Random, Missing At Random, and Missing Not At Random

• Multiple Imputation

• Monotone and intermittent missingness

This workshop consists of 4 x 1.5 hour sessions in PowerPoint, and 4 x 1.5 hour practical sessions in SPSS.

This workshop is intended for non-statisticians and statisticians new to the field of longitudinal data analysis. A basic knowledge of Regression is assumed.

These workshops are designed for a broad range of participants, researchers from various application fields who only spend a small portion of their time doing statistics (but researchers who when they do statistics want to be doing statistics well). Communicating complex statistical ideas to a non-statistical audience requires significant skill. Equations for example are vital for statisticians who want to describe statistical models accurately but succinctly, however these equations can be a stumbling block for a larger audience who are not used to working with complex equations. We think one sign of a good statistician is that they know the pictures that go on behind the equations, and in our workshops we focus on the pictures rather than the equations.

Working with this broad audience we teach complex statistical theory (we find it heart-breaking when excellent research studies are undone by a poor understanding of underlying statistical theory), but we teach this theory using a number of practical real-world examples. We are also a strong believer in the use of humour in a training context, where humour means that participants are more likely to relax in a training context, to engage with the training content and the presenter, and are more comfortable to ask the questions that they really want to ask about the content as a result.

Each workshop will be capped at 20 participants.