search for: comorbidity

Dear R-listers, I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model I want to compare the discriminative ability of my comorbidity measure with the "old" comorbidity measure, Charlson's Comorbidity Index. I have nearly 10...

I am reposting my message from April 8th because I never received a response to the original post: Dear R-listers, I am an MD and clinical epidemiologist developing a measure of comorbidity severity for patients with liver disease. Having developed my comorbidity score as the linear predictor from a Cox regression model I want to compare the discriminative ability of my comorbidity measure with the "old" comorbidity measure, Charlson's Comorbidity Index. I have nearly 10...

If there are any other users who use AHRQ's SAS code comoanaly2010 and comformat2010 to create comorbidity variables, I thought you might be interested in the following PRELIM code we wrote to mimic its functionality in R. It seems to yield similar results, but may contain errors. Please feel free to comment (kindly) or enhance. I'm sure there are better ways to skin this cat, but we at least took a...

I downloaded data from http://www.hcp.med.harvard.edu/ncs/ Which provides data in DTA (STATA), XPT (SAS), and POR (SPSS) formats all of which I have tried to read with the foreign package but I am not able to load any of them. I have 2 gb of RAM, but R crashes when the memory gets just over 1 GB. I am using Windows version 2.1.1. The size of the DTA file is 48 MB; the xpt file is 188

...m running into some trouble with using the fastbw() function breaking up natural groups of variables. Is there any way I can specify to keep certain variable together? In particular, if interactions are included I would also like to keep the main effects in the model. Another example is a group of comorbidity variables that I would like to be assessed all together and not as separate components as this makes more sense from the perspective of interpretation. The Force = ... option seems to only work for pre-specified variables and does not solve my problem. In the case of the comorbidites, the variable...

Hi all, I'm using the medical risk package to determine the risk stratification Index based on the ICD9 codes. Although, I have been successful in using it, I'm unable to interpret the output. here is the sample code # Calculate RSI for each patient ("id") in dataframe cases <- data.frame(id=c(1,1,1,2,2,2,2,2), +

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