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A very nice resource that talks about difference scores, relative change models, analysis of covariance, and repeated measures models. Continue reading
This page promotes a new approach to a broad class of models (spatio-temporal models, latent variable models, mixed models) using a fast approximation to the Bayesian solution. It runs under R and appears to handle very large datasets. I have not had a chance to try this, but it looks very interesting. Continue reading
Someone asked me how to calculate a 90 day readmission rate from a large database. It’s a tricky problem because for many databases, it requires you to examine the data from a longitudinal perspective. Here’s some general advice. Continue reading
I am working on a class that will teach basic data management and graphics using the R programming language with parallel classes in SPSS and SAS. On the third or fourth day of the class, we will look at managing longitudinal data sets, as these require special skills. I wanted to find a couple of reasonably simple longitudinal data sets that were available on the web and which had at least a few missing values in them. Here’s a couple of data sets that might work. Continue reading
This site provides description of a free software package, MLPowSim, that calculates power for complex random effects models. It was developed by the Centre for Multilevel Modelling, the same group that developed the LMwiN package for analysis of complex random effects models. Continue reading
In studies with a baseline, examining the decline exclusively within the treated group, or examining the decline in the treated group and then separately examining the decline in the control group is a bad idea, notes two famous statisticians in the British Medical Journal. They explain why you need to look first at comparisons between the two groups, ideally with analysis of covariance. Continue reading