Hi everyone,

Online, once again!

Our October session will be on 21st, so join us from 5.30pm online. As usual, the meeting will be open for all to attend, and newcomers / beginners are very welcome.

Our online meetings are kindly being enabled by Red Hat. In order to join us you need to register with MeetUp.

Our speakers are Lydia Gabriela Speyer and Russ Hyde.

  • Lydia Gabriela Speyer is a third year PhD student at the University of Edinburgh. Her research focuses on analysing longitudinal data such as the Millennium Cohort Study using Structural Equation Modelling and Network Analysis to gain insights into the effect of perinatal environmental and genetic risk factors on children’s socio-emotional development.
  • Russ Hyde started using R a decade ago, while a bioinformatician at Liverpool uni. In recent years, he has presented at Edinbr on the packages dupree and polyply. He mentors at the “R for data science” community and helps maintain lintr. Having left bioinformatics, Russ is currently looking for data science/engineering jobs; but is mostly fixing up a house.

Analysing Dynamic Change in Longitudinal Data using ALT-SR and GVAR models

Lydia Gabriela Speyer

This talk will give a short introduction to using Autoregressive Latent Trajectory Models with Structured Residuals and Graphical Vector Autoregression Models to analyse dynamic change in longitudinal panel data using R. These models focus on disaggregating within from between-person effects when modelling concurrent and temporal inter-relations between multiple repeated measures variables simultaneously. The two methods will be illustrated using data on children’s socio-emotional development from the Millennium Cohort Study.

Your Code As Data

Russ Hyde

The code you write this month won’t stay still. You’ll eventually want to add extra features to that package or extra analyses to that project. You might find a bug or try to speed things up. Your tests might start to fail when dependencies change or your report might not build on a different system. As it evolves to accommodate these changes, it is worth reappraising your code. R has a range of tools to help assess your current code-base encompassing static analysis (style / syntax / structure: lintr, goodpractice, cyclocomp, pkgnet) and dynamic analysis (test coverage / benchmarking / profiling: covr, bench, profvis). For version-controlled projects, the git history can provide an archaeological and social view of the code base that complements analysis of the code itself. In this talk (inspired by Adam Tornhill’s book ‘Software Design X-Rays’), I show how existing R tools for working with git can be combined with code analysis tools to provide a rich dataset about your code.

October 2020 meeting: longitudinal data and appraising your code

Our speakers are Lydia Gabriela Speyer and Russ Hyde.

See you there!


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