[R] test deviation from a binomial distribution - lack of 50:50
parn at nt.ntnu.no
parn at nt.ntnu.no
Mon Apr 23 18:47:21 CEST 2007
Dear R-users,
I have a data set where each observation consists of a number of trials
(n.trials) that varies between 5 and 7, 6 being most common. Each trial
can take either of two outcomes, success or failure.
A dummy data set:
n.trials <- sample(5:7, 50, replace=T, prob=c(0.2, 0.6, 0.2))
success <- rbinom(50, n.trials, p=0.5)
failure <- n.trials - success
I know I could test for a deviation from 50:50 success:failure in one or
the other direction using a glm with binomial errors. However, I
suspect that in my 'real' data set the outcome 50:50 is
underrepresented, not due to a skew in one particular direction, but
rather that within each observation there are either many successes or
many failures. Although I did not manage to create a dummy data set
with these properties, which would be the proper way in R to test for a
'lack of 50:50 outcome' using the simple dummy data above as a starting
point?
Thanks in advance!
Henrik
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