specifying model with multiple interactions
I am having trouble specifying a mixed effects model and would appreciate some guidance. Background We are interested in how cricket batsmen respond to balls delivered from bowling machines. We filmed batsmen facing deliveries at different speeds from a bower and machine. The data is very expensive because each video has to be digitized by hand to identify various parameters of interest. Hence we only have data on 13 subjects (and it has missing values). One objective is to predict the timing of bat lift (BatUp) by delivery speed (Speed) for a given condition (Delivery) and to assess the variability across subjects (Subject). Delivery : Factor w/ 2 levels "Bowler","Machine" Subject : Factor w/ 13 levels Speed : num BatUp : num So I believe I want to predict a fixed effect for speed and random slope and intercept for each level of a factor created by Subject:Delivery I'm getting a bit confused with the combinations of random effect. I have read through a few of the chapters of Doug Bates. (2010). lme4: Mixed-effects modeling with R. This is as far as I have got... BatUp ~ Speed + (1|Delivery) + (1|Subject) + (1|Subject:Delivery) + (0+Speed|Subject:Delivery) Thanks in advance for any help. Regards, James Regards, James ________________________________________ James Croft, PhD Research Fellow Sport Performance Research Institute New Zealand School of Sport and Recreation AUT University Private Bag 92006 Auckland 1142 New Zealand Phone 64-9-921 9999 ext 7685 Fax 64-9 921 9960 Email james.croft at aut.ac.nz http://www.isrrnz.ac.nz/