[R-sig-ME] MCMCglmm and proportion time data
Marcus Michelangeli
marcus.michelangeli at monash.edu
Thu Mar 17 08:03:47 CET 2016
Hello,
Apologies if a similar question has been asked and answered before, but any
help would be extremely appreciated
I measured 4 behavioral traits in the same test over a period of 20
minutes. Each individual went through the test three times so I could
estimate repeatability.
EXAMPLE DATASET
SKINK TRIAL POPULATION REGION ACTIVE BARRIER SHELTER STILL
1 SKINK22 1 Kuring-gai Chase N 1134.08 575.38 0.00
630.90
2 SKINK22 2 Kuring-gai Chase N 246.28 59.61 657.57
896.12
3 SKINK22 3 Kuring-gai Chase N 281.60 24.68 118.87
1381.20
4 SKINK23 1 Kuring-gai Chase N 0.00 0.00 1799.97
0.00
5 SKINK23 2 Kuring-gai Chase N 279.89 0.00 634.61
885.47
6 SKINK23 3 Kuring-gai Chase N 20.77 0.00 1243.55 535.65
When looking at histograms of each behaviour, the data is heavily skewed to
the left and is obviously non-normally distributed (all distributions look
exponential)
I'm not sure how to tackle this. I basically just want to estimate the
repeatability of each behavioural trait and look at the effects of Region
and Population on behaviour. I'm think my best option is to convert the
data into proportions (i.e. what proportion of time did the individual
spend doing each behavior over the 20 mins) and then run a GLMM (preferably
using MCMCglmm in R or glmer) with a binomial distribution. My questions are
1. Would this be the best way to tackle this data?
2. What distribution should I use in MCMCglmm (is it family "categorical")?
3. Do binomial distributions require different priors. I usually just use
an uninformative prior (V =1, nu =0.002)
Thanks for your time
Marcus
[[alternative HTML version deleted]]
More information about the R-sig-mixed-models
mailing list