search for: sms13+

Excuse the simple question... I'm not sure what I'm doing wrong with predict, but let me use this example: Suppose I do: dat<-matrix(c(0,0,10,20),2,byrow=T) lm1<-lm(dat[,2]~dat[,1]) Suppose I want to generate the linearly-interpolated y-values between the point (0,0) and (0,20) at every unit interval. I thought I just do: predict(lm1, data.frame(seq(0,10,1))) to get

I have a dataframe that contains fields such as patid, labdate, labvalue. The same patid may show up in multiple rows because of lab measurements on multiple days. Is there a simple way to obtain just the first and last record for each patient, or do I need to write some code that performs that. Thanks, Steven

Please excuse what I'm sure are very easy questions but I'm relatively new to the R environment. How can I view a range of list elements, but not all. e.g., I had a matrix of patients and then split them out by patient id. I know I can do patlist[[1]] to see the first one, but how can I view, say, the first ten patients? My other question is how to count how many patients have a

I was wondering if someone can tell me the best way to search through a matrix and choose certain rows (based on certain conditions) to put into a separate matrix. What I have tried so far is very slow for a large dataset I'm working with. e.g., I have this piece of code to create a new matrix (newmat) based on my filtering conditions. Do I need to do this kind of thing where I keep

I was wondering if someone can help me figure out the following: I have two patient datasets, ds1 and ds2. ds1 has fields "patid", "date", and "lab1". ds2 has "patid", "date", and "lab2". I want to find all the patids that have at least 2 dated records for each lab. I started by splitting each dataset by patid, to create ds1.list

I have used the 'par' command to overlay one plot on another. But how do I overlay it with the x-values plotted at the same points on the x-axis? Thank you, Steven

...utput. I see that it gives the Scale parameter. How do I find the Shape paramater as a function of the covariate? Thank you, Steven --------------------------------------- ------------------------- Steven Shechter PhD Candidate in Industrial Engineering University of Pittsburgh www.pitt.edu/~sms13

Hi, I was wondering if someone can help me interpret the results of running weibreg. I run the following and get the following R output. > weibreg(Surv(time, censor)~covar) fit$fail = 0 Call: weibreg(formula = Surv(time, censor)~covar) Covariate Mean Coef Rel.Risk L-R p Wald p covar 319.880 -0.002 0.998 0.000 log(scale) 0.000 8.239

Hi, If I set df=2 in my smooth.spline function, is that equivalent to running a linear regression through my data? It appears that df=# of data points gives the interpolating spline and that df = 2 gives the linear regression, but I just want to confirm this. Thank you, Steven