similar to: cox model test heterogeinity

I'm a french medicine student and i work on oncology. I work about treatment oh breast cancer. I have 3 sub group of patient. I made some kaplan meyer survival curve, and i made a cox model. On the survival curve, on the last observations there is a crossmatch of the different survival curve at 150 month . I study the validity of my model by study of residual by study the proportional risk.

Hi i'm a french medical student, i have some data that i import from excel. My colomn of the datafram are the localisations of metastasis. If there is a metatsasis there is the symbol "_". i want to exclude the row without metastasis wich represent the NA data. so, i wrote this mela is the data fram mela1=ifelse(mela[,c(11:12,14:21,23,24)]=="_",1,0) # selection of the

Hello, i'm a french student of medical oncology and i'm working on breast cancer. I have a variable with the histologic type of tumor wich is between 1 and 5. I use as.factor function to make some variable with level between 1 and 5. When i put it in the cox model i have only the level between 2 and 5. The level 1 doesn't appear. I think i have to change the number of level but i

Dear list, I am trying to build a cox model and then perform ROC analysis in order to retrieve some genes that are correlated with breast cancer. When I calculate the hazard score taking into account different numbers of genes and their coefficients ( I am trying to find the pest predictor number of genes), I retrieve from around 1 values (for few genes included ) to size of e+80 values (for many

Hi Paul, No need to collapse the information into a single text string, gregexpr() can take a vector of strings (sentences in your case). You can split your sentences up, number them how you want, then search for your pattern either via regex or via these extra packages you use which probably use the PCRE regex library anyway. However, as this is basically what you did, I'm not sure why

Hi Robert, Thank you for your reply. An attempt to solve this via a regular expression query is particularly helpful. Unfortunately, I don't have much time to play around with this just now. Ultimately though, I think I would like to implement a solution something along the lines of what you have done. I have a book on regular expressions that I am now starting to read. In the meantime, the

Dear R-help list, Apologies. I am trying to convert one table to another. It feels that it should be a very straightforward answer with a single (or two) commands with the right extensions, but I really can't figure this out right now. I have several hundred pheno factors actually, so manually doing this line by line is not an option. My original table is approximately like this : ID

Hello friends and fellow R users, I have a problem to which I have been unable to find a solution: I am gathering survival data on patients undergoing treatment with a new kind of stent. I want to generate survival data and plot survival curves of these patients based (among other things) on the treating physician. My data set has been tabulated in the following manner: Date (the date the stent

Hi Paul, Sounds like you have your answer, but for fun I thought I'd try solving your problem using only a regular expression query and base R. I believe this works: > txt <- "Patient had stage IV breast cancer. Nothing matches this sentence. Metastatic and breast match this sentence. French bike champion takes stage IV victory in Tour de France." > pattern <-

Hi group, My case has N physicians with each seeing M patients. One physician could have seen a group of patients, or, a patient could have been seen by multiple number of physicians. In order words, there are overlaps. Now, I have the following NxM matrix Patient#1 Patient#2 Patient#3 ....... Patient#m Physician#1 1 0 1 ....... 0 Physician#2

Have you looked at the CRAN Natural Language Processing Task View? If not, why not? If so, why were the resources described there inadequate? Bert On Jul 11, 2017 10:49 AM, "Paul Miller via R-help" <r-help at r-project.org> wrote: > Hello All, > > I need some help figuring out how to extract combinations of target > words/terms from cancer patient text medical

COMPUTATIONAL ANALYSIS OF NEXT GENERATION SEQUENCE DATA (http://bioinformatics.nki.nl/vacancies.php) THREE BIOINFORMATICS POSITIONS PROJECT OUTLINE Genomic alterations are major determinant of responses to (targeted) therapies in cancer. In fact, the best positive and negative predictors of responses to targeted therapies are alterations in kinases or their direct downstream effectors. To

Hello All, I need some help figuring out how to extract combinations of target words/terms from cancer patient text medical records. I've provided some sample data and code below to illustrate what I'm trying to do. At the moment, I'm trying to extract sentences that contain the word "breast" plus either "metastatic" or "stage IV". It's been some

I am trying to model a clusterd ordinal response data (either 1, 2 or 3) called , the correponding physician of the patient is also in the data. Since it is ordinal, I used the ordinal logit model topbox[i]~discrete with probability P[j,1],p[j,2], p[j,3], j is the corresponding physician of the ith patient C[j] is the physician effect , a1 and a1+theta is the common cutpoints for all

I tried thinning of the mcmc run with 500,000 iteration. It looks like 100 or 200 is enough to remove the autocorrelation of a1 and tau. Is that too much thining? --- On Tue, 3/16/10, ping chen <chen1984612 at yahoo.com.cn> wrote: > From: ping chen <chen1984612 at yahoo.com.cn> > Subject: an ordinal regression MCMC run high correlation > To: r-help at r-project.org >

Hi Bert, Thanks for your reply. It appears that I didn't replace the variable name "sampletxt" with the argument "x" in my function. I've corrected that and now my code seems to be working fine. Paul ________________________________ From: Bert Gunter <bgunter.4567 at gmail.com> Cc: R-help <r-help at r-project.org> Sent: Tuesday, July 11, 2017 2:00 PM

Dear group, I am trying to use gamm() in mgcv. Here's the scenario. The data frame has approx. 110K observations with information on paediatric readmission binary outcome (Y/N) and total volume of their most responsible physician as the covariate. Since any physician can have multiple patients, the data contains clustering structure which I am trying to account for. My original formula is

I'm looking for software that makes plots such as fig 4 (a)-(e), fig 5 anf fig 7 of Gray, Robert, "Flexible Methods for Analyzing Survival Data Using Splines, with Applications to Breast Cancer Prognosis," 1992, J Am Stat Assoc, pp 942-51. In other words, I'm looking for software that takes survival data and a continuous covariate as input and computes a curve giving log hazard

I'm puzzled by the behaviour of factors in rma models, see example and comments below. I'm sure there's a simple explanation but can't see it... Thanks for any input John Hodgson ------------------------------------- code/selected output ----------------- library(metafor) ## Set up data (from Lenters et al A Meta-analysis of Asbestos and Lung Cancer... ##

I have an online doctor/dentist search. Right now I have all the code in one controller, with separate views and actions for the doctor and dentist. About 80% of the code in both the controller and the view is shared. Doctors and dentists are in separate tables with different (yet very similiar) schema''s. So the sql queries are different, and some of the information displayed in the