I ran into this presentation on Statistical aspects of two-way cross-over studies by Ing. Helmut Schütz (http://bebac.at). He presented some code and referred to the bear package. The bear package is menu driven, which is not my thing. I had to try and do that in R ... [Read more...]

Based on some comments I am looking at using symmetry to obtain Williams style designs. Symmetry allows reduction of the number of combinations examined hence faster calculation times. Two avenues are examined. Both work for a low number of treatments.... [Read more...]

Those are Williams designs you might say, but it has become clear to me that Williams designs are just a subset of all carry-over balanced designs. Not through hard work of mine, comments by Apn on my previous post Creating Williams designs with e... [Read more...]

The last couple of days I read a number of times about stabilization in house prices which had been dropping due to the crisis. And you get hit by numbers such as change against Q2 2013 or Q3 2012. These are accompanied by reasons why this or that quarter may be special ... [Read more...]

I am trying exercise 59.8 (page 5057) of the SAS/STAT Users Guide 12.3 in R. The interesting thing is that influence is investigated on subject level rather than individual level. The diagnostics in nlme does not do leave-subject-out, at least, not tha... [Read more...]

In this post I extend my knowledge of mixed models by redoing section 59.7 (page 5048) of the SAS/STAT user guide. I don't think this particular example can be run in lme4, so that leaves nlme and MCMCglmm. MCMCglmm has less ability for influence measu... [Read more...]

Reddit has a subreddit Guns are cool which in turn contains the MASS SHOOTINGS IN 2013 page. I pulled those data to see if there was anything of interest to plot or examine. I ended with modelling the frequency of shootings (once a day, Poisson distribution), and number of victims per ... [Read more...]

Continuing from random coefficients part 1, it is time for the second part. To quote the SAS/STAT manual 'a random coefficients model with error terms that follow a nested structure'. The additional random variable is monthc, which is a factor con... [Read more...]

Continuing with my exploration of mixed models I am now at the first part of random coefficients: example 59.5 for proc mixed (page 5034 of the SAS/STAT 12.3 Manual). This means I skipped examples 59.3 (plotting the likelihood) and 59.4 (known G and R)... [Read more...]

Continuing my exploration of mixed models, I now understand what is happening in the second SAS(R)/STAT example for proc mixed (page 5007 of the SAS/STAT 12.3 Manual). It is all about correlation between the time-points within subjects. The data as suc... [Read more...]

Last week I tried exercise 1 of the SAS(R) proc mixed with R libraries lme4 and MCMCglm. So this week I aimed for exercise 2 but ended up redoing exercise 1 with nlme.Exercise 2 results gave me problems with library lme4 and latter parts of the ex... [Read more...]

I want to build a bit more experience in REML, so I decided to redo some of the SAS examples in R. This post describes the results of example 59.1 (page 5001, SAS(R)/STAT User guide 12.3 link). Following the list from freshbiostats I will analyze ... [Read more...]

I wanted to have a look at various REML methods for a long time. The rainfall data seemed a nice example. On top of that, FreshBiostats had a blog post 'Mixed Models in R: lme4, nlme, or both?'. So lme4 it is.The data  As described before; th... [Read more...]

Two weeks ago I showed rain data from six stations in Netherlands years 1906 till now. Last week I showed that frequency of days with and without rain differed between December 1906-1915 and December 2003-2012. This week I am considering the ... [Read more...]

Last week I showed rain data from six stations in Netherlands years 1906 till now. The obvious next question is; did it change? A surprisingly difficult question. The data is not normal distributed, but it is time-correlated, location correlated.T... [Read more...]

Climate has my interest. But discussions on climate change seem to be focused on temperature. In real life, we look at temperature, rain, sunshine and wind. I was therefor happy to find a load of rain data on Royal Netherlands Meteorological Institute.... [Read more...]

Based on last week's faster algorithm I wanted to finish with car weights. Unfortunately a fail again. By now it is a fail of myself, it needs a bit more dedication and grunt than I am willing and able to give for this blog. This week I added... [Read more...]

Last week I decided to speed up my distribution fitting functions of two weeks ago. These were bold words. My try of Rcpp was a failure. Just plain optimization helped a bit better. Using the compiler package added a bit. (the compiler package does not... [Read more...]

I wanted to extend my car weight distribution calculation of June 16 from only 2000 to years 2000 to 2013. Unfortunately, come Sunday afternoon the code seemed too slow and not even the beginning of a post. So, I went on to another calculation I w... [Read more...]

Two weeks ago I described car data, among which weight distribution of cars in Netherlands. At that time it was purely plots. In the mean time I decided I wanted to model trends. As a first step of that, I decided to fit distributions for these da... [Read more...]