This is a pretty simple R coding problem, just want to make sure I got it right. Thumbs up and good recommendation for anyone who can help!

(2) For 10 coins, let #, denote the probability of a head for coin i. You flip each coin 5 times. The sample numbers of heads are (2,4,1,3,3,5,4,2,3,1) (a) If we are interested in estimating #, does it make more sense to use a GEE or a GLMM for this model? (b) Fit a random effects model to this data and obtain predicted values ( 7,} (c) Make a plot to compare the predicted probabilities from (b) and the sample proportions. What do you see? (d) Suppose now that the true values are