Following on from some of my earlier posts, this is purely about, hopefully, saving some other people some time in putting this together. Height z-scores are required to then calculate the blood pressure z-scores. The CDC (Center for Disease Control … Continue reading →
Like every year, August sees the thousands taking part in the Perth City to Surf, and with that comes the chance for some stats. Why? Curiosity more than anything, and to convince myself that my time in the 12km run … Continue reading →
Following on from my earlier post on creating a table of ICD codes in R, here is how I am currently counting these codes and storing the codes in a dataframe: Firstly create a dataframe to store the results in: hosp_count <- as.data.frame(matrix(ncol=length(icd_codes))) names(hosp_count) <- names(icd_codes) Counting Occurences: Then start to loop through your dataset with 
A brief first post on what I hope will be a series of posts on analysing hospitilisation data, which is recorded using ICD codes (International Statistical Classification of Diseases and Related Health Problems) Initially here is an R file. This can be read in and will create a list, 218 long, forming groupings using sub 
Thanks to this great post http://www.imachordata.com/?p=730 we can now put multiple plots on a display with ggplot2. This provides somewhat similar functionality to ‘par(mfrow=c(x,y))’ which would allow multiple plots with the base plot function. gridExtra doesn’t have quite the same level of options as ‘par’, but the syntax is simple. grid.arrange( graph1, graph2, ncol=2 Simple. ‘grid.table’ 
Recently I was asked to help create random IDs for someone. At first I thought, ‘Ah yup, 1:x (1,2,3, …,x), job done’. Then I thought that there had to be a R function/package to create better looking IDs, to which I didn’t find one, if there is, please let me know. In the mean time 
This one does my head in. I do it fairly regularly, lots of people do, but I find everytime it comes to interpreting the results I have to slow it right down and go step by step. Answer: When you log the outcome, then on the original scale, for all else constant, Y will be 
Not my post, just bookmarking this. It’s from http://goanna.cs.rmit.edu.au/~fscholer/anova.php ANOVA (and R) The ANOVA Controversy ANOVA is a statistical process for analysing the amount of variance that is contributed to a sample by different factors. It was initially derived by R. A. Fisher in 1925, for the case of balanced data (equal numbers of observations 
This is a great post, very true, not enough of R’s graphics are well displayed online to really see how to achieve what the often ambiguous ‘help’ information suggests. http://research.stowers-institute.org/efg/R/Graphics/Basics/mar-oma/index.htm I particularly find “mtext(“lol”, outer=T)” to be particularly useful (requires “oma=c(2,2,2,2)” or similar). http://addictedtor.free.fr/graphiques/ This site is somewhat of the way there, but I’ve found 
In analysis of Child Health data, generally z-scores or percentile groupings are used as children do not growth is not linear. The CDC (Center for Disease Control and Prevention) have released tables of data for calculating these z-scores and percentiles, and here are some scripts for R to calculate these in your sample. CLICK HERE 
Zero Inflated Models and Generalized Linear Mixed Models with R.
Zuur, Saveliev, Ieno (2012).
