It’s been a long time since I last created a new post here in PSYCTC.org but I see I had this title lying around. Time to use it!

I’ve been pretty busy with CORE work but also putting quite a lot of time into building non-CORE resources and I think it really is time to put something about them here.

The first has been around for a long time and is a glossary that started as an online glossary for the OMbook. I’m up to 266 entries as of today, 26.iii.24, there’s a focus on quantitative methodology and I have tried to explain terms that I think often get thrown around to impress or without people really knowing what they mean (Multilevel Models/Modelling (MLM) perhaps) or are a bit esoteric (Anderson-Darling test anyone?) Give the list with its search box a look. Tell me if you want other things in there or existing definitions improved.

Then there are two things that complement the glossary but also stand on their own:

- My Rblog. This is a set of static pages that allow much more space to explain some things in the glossary but also has pages for other, mostly statistical, occasionally geeky things. As the name suggests, quite a few of them explain things about using the R statistics system but many of them simply stand alone. Try Explore distributions with plots or Jacobson #1 gives an introduction to Jacobson (RCSC) plots.
- My shiny apps. These are interactive: you can put your own values or data in. The early ones were fairly simple: e.g. saving you computing the RCI for your SD and reliability yourself, similarly for the method c CSC (but that has a nice graph as well as the CSC). There are a number that give you confidence intervals (CIs) around observed statistics if you input the statistic, the dataset
*n*and width of the interval you want (usually 95%). So far I’ve created apps of that type for observed means, proportions, differences between two proportions, SDs or variances, Pearson correlations, Spearman correlations and for Cronbach alpha values. One I particularly like gives you CIs for quantiles if you paste in your data and the quantiles you want. I like the graph that goes with that one! Then are some that are demonstrations of issues such as screening and the Bonferroni correction. Finally, and just this last week, I have cracked interactive uploading of data in CSV, R, spreadsheet and SPSS formats. That starts with a fairly simple app that gives you the histogram of your data and its summary statistics (allowing you to download the plot in various formats).

I’ve got my CEPCfuns: a package of R functions for therapy, MH & WB data analyses but that’s pretty geeky though should be useful to anyone who already uses R. More on that another time.