[R] binomial logistic regression question

[majesty]

Dear subscribers, 

I am looking for a function which would allow me to model the dependent
variable as the number of successes in a series of Bernoulli trials. My data
looks like this

ID  TRIALS     SUCCESSESS   INDEP1 INDEP2 INDEP3
1      4444        0                0.273     0.055  0.156
2      98170      74               0.123     0.456  0.789
3      145486    30               0.124     0.235  0.007
4      147149    49               0.888     0.357  0.321
5      60585      11               0.484     0.235  0.235
6      198953    43               0.295     0.123  0.856

I want to find out how independent variables influence the number of
successful trials (dependent variable)
I had tried to use glm formula 

regression.glm <- glm( SUCCESSESS ~ INDEP1 + INDEP2 + INDEP3, data = data,
family = binomial, weights= TRIALS) 

but got the following: Error in eval(expr, envir, enclos) : y values must be
0 <= y <= 1
but there y has to be between 0 and 1 (which does make sense, but that's why
I am using weights?)

I would be grateful for any hints/suggestions on how to proceed.
Cheers, 
Juta


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