search for: dosered

Hello list, I want to make a large rulebased algorithm, to provide decision support for drug prescriptions. I have defined the algorithm in a function, with a for loop and many if statements. The structure should be as follows: 1. Iterate over a list of drug names. For each drug: 2. Get some drug related data (external dataset). Row of a dataframe. 3. Check if adaptions should be made to

...n a meta-analsysis and all the forest (meta) and forestplot (rmeta) instructions assume you are doing a meta-analysis. I found rmeta didn't play nicely for me so I'm using the meta package with forest. Here's some code that would allow you to reproduce it: library(meta) mydata.forest.DoseRed = data.frame(c(1,7,14,6,16), c(7,21,10,15,23), c(1,1,5,2,5), c(4,7,6,5,12)) colnames(mydata.forest.DoseRed)=c("n.DR","n.No.DR", "E.DR","E.No.DR") rownames(mydata.forest.DoseRed)=c( "Age: 50-59", "Age: 60-69 ", "Age: >70", &q...

Dear Rxperts, Running the following code: ======================================================= twlo=10; twhi=20; wt=154; vd=0.5; cl=0.046; tau=6; t=3; F=1; wtkg <- wt/2.2 # convert lbs to kg vd.pt <- wtkg * vd # compute weight-based vd (L) cl.pt <- wtkg * cl # compute CL (L/hr) k <- cl.pt/vd.pt # compute k (hr^-1) cave <-

Dear Colleagues, Our group is also working on implementing the use of R for pharmacokinetic compartmental analysis. Perhaps I have missed something, but > fit <- nls(noisy ~ lsoda(xstart, time, one.compartment.model, c(K1=0.5, k2=0.5)), + data=C1.lsoda, + start=list(K1=0.3, k2=0.7), + trace=T + ) Error in eval(as.name(varName), data) : Object