search for: g_smits

I just noticed that two key pieces of information are not given by the summary() command: N and SD. we are given the N missing, but not the converse. I know these summary value can be obtained easy, but can't understand why these two pieces of information are not provided with the other info. Thanks, Gerard

Hi R users, I have a test dataframe ("file1," shown below) for which I am trying to create a flag for the first and last ID record (equivalent to SAS first.id and last.id variables. Dump of file1: > file1 id rx week dv1 1 1 1 1 1 2 1 1 2 1 3 1 1 3 2 4 2 1 1 3 5 2 1 2 4 6 2 1 3 1 7 3 1 1 2 8 3 1 2 3 9 3 1 3

All, I would like to find a simper method that I now have to find the product of all elements in a vector: #get product of vector elements: (1,2,3,4,5) vec.product <- exp(sum(log(c(1,2,3,4,5)))) I have not found a vector product function, if one has been written. Thanks, Gerard [[alternative HTML version deleted]]

All, I am trying to put a few special symbols into a string to place on a graph (e.g., >= and superscript 2). This clearly works, but does not look good: text<-c("x2", "A>=B") I tried pasting in the >= symbol, but just comes out as an =. I have tried expression() with no luck: text<-c("x2", expression(x^2)) Any help appreciated. Thanks,

Hi All, I'm trying to label my plot axis with times (HH:MM) that correspond to a numeric index (values 0:6) for my time variable. I'd like to plot "08:00", "12:00", and so on, instead of 0 through 6. I have used the following line of code: axis(1, 0:6, labels=c("08:00", "12:00", "16:00", "20:00", "24:00",

Hi All, I have a small dataset named das (43 cases) in which I am trying to create a binary outcome (1/0) based on the following code: if (das$age>65 && das$bmi>30) {das$danger<-1} else das$danger<-0 I am setting a flag called 'danger' to 1 of the subject is over 65 and has a BMI > 30. I find that my statement evaluates the first record in the data.frame and

Hi All, I am running a scatter plot and trying to add a best fit line. I use an abline function, but get no line drawn over the points. I also get no error. I arm using V 2.10.0 on Windows 7. Here is my code, including the SAS transport file import: require (foreign) require (chron) require (Hmisc) require (lattice) clin <- sasxport.get("y:\\temp\\subset.xpt") attach(clin)

I have an attached data.frame with a binary composite variable (comp) and a predictor (egfr). I am trying to plot a restricted cubic spline using: require (Hmisc) require (Design) rcspline.plot(x=egfr,y=comp,model="logistic",nk=5,knots=NULL, xlab="label1", ylab="Label2", plim=c(0,1), plotcl=TRUE, showknots=TRUE,

Like many others, I am new to R but old to SAS. Am I correct in understanding that R processes a data frame in a sequential ly? This would imply that large input files could be read, without the need to load the entire file into memory. Related to the manner of reading a frame, I have been looking for the equivalent of SAS _n_ (I realize that I can use a variant of which to identify an index

All, I am using the forestplot function in rmeta. I was able to modify the x axis range by commenting out one line and feeding it two new parameters (I wanted to set zero as the axis start point). #xrange <- c(max(min(lower, na.rm = TRUE), clip[1]), min(max(upper, na.rm = TRUE), clip[2])) #new line xrange <- c(xlow,xhigh) Now I am trying to modify the text font size for

Hi All, There are a variety of functions that can be applied to a variable (column) in a data frame: mean, min, max, sd, range, IQR, etc. I am aware of only two that work on the rows, using q1-q3 as example variables: rowMeans(cbind(q1,q2,q3),na.rm=T) #mean of multiple variables rowSums (cbind(q1,q2,q3),na.rm=T) #sum of multiple variables Can the standard column functions (listed in the

Hi All, I have been able to modify the x-axis to start at zero by adding xlow and xhigh parameters; that was pretty simple. I have been unable to find the location of the code that would turn off the information weighting of the box size (I have smaller randomized trials getting less weight than a much larger non-randomized trial). The function is forestplot() from rmeta. Thanks for any