similar to: How to run coxph() with time dependent cohort sampling

> Now that we have case cohort model , we have 1000 people and 50 cases > Let the first 10 cases occur at the same time > second 10 " > third 10 " > fourth 10 " > fifth 10 " > How easy is it to randomly sample 50 different > cohort controls for each group? >That

I tried to compare if cch() and coxph() can generate same result for same case cohort data Use the standard data in cch(): nwtco Since in cch contains the cohort size=4028, while ccoh.data size =1154 after selection, but coxph does not contain info of cohort size=4028. The rough estimate between coxph() and cch() is same, but the lower and upper CI and P-value are a little different. Can we

--------- begin included message --------- I tried to compare if cch() and coxph() can generate same result for same case cohort data Use the standard data in cch(): nwtco Since in cch contains the cohort size=4028, while ccoh.data size =1154 after selection, but coxph does not contain info of cohort size=4028. The rough estimate between coxph() and cch() is same, but the lower and upper CI

Hi. I've a dataframe with about 46000 women with about 500 cases (cancers). I want to define a case-cohort sampling scheme, matching by age and hospital centre. Is there anyone who has already written a code for that? It should be something similar to the stcacoh macro in Stata. TIA, Stefano -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list

Hi In case cohort study, we can fit proportional hazard regression model to case-cohort data. In R, the function is cch() in Survival package Now I am working on case cohort analysis with time dependent covariates using cch() of "Survival" R package. I wonder if cch() provide this utility or not? The cch() manual does not say if time dependent covariate is allowed I know coxph() in

Hi, I ran the example on pp. 799-800 from Machael Crawley's "The R Book" using package survival v. 2.36-5, R 2.13.0 and RStudio 0.94.83. The model is a Cox's Proportional Hazards model. The result was quite different compared to the R Book. I have compared my code to the code in the book but can not find any differences in the function call. My results are attached as well as a

I have a study best described as a retrospective case-cohort design: the cases were all the events in a given time span surveyed, and the controls (event-free during the follow-up period) were selected in 2:1 ratio (2 controls per case). The sampling frequency for the controls was about 0.27, so I used a weight vector consisting of 1 for cases and 1/0.27 for controls for coxph to adjust

----- begin included message In case cohort study, we can fit proportional hazard regression model to case-cohort data. In R, the function is cch() in Survival package Now I am working on case cohort analysis with time dependent covariates using cch() of "Survival" R package. I wonder if cch() provide this utility or not? The cch() manual does not say if time dependent covariate is

Hello, I am interested in producing the expected number of events, in a recurring events setting. I am using the Andersen-Gill model, as fit by the function "coxph" in the package "survival." I need to produce expected numbers of events for a cohort, cumulatively, at several fixed times. My ultimate goal is: To fit an AG model to a reference sample, then use that fitted model

Jin Wang had an error. My original note specified a variable that was 1 for subjects NOT in the subcohort, so the correct coxph call is coxph(Surv(edrel, rel) ~ stage + histol + age + offset(-100*(subcohort==0)) + cluster(seqno), data =ccoh.data) This gives the same coefficients as the cch example, along with the infinitesimal jackknife or "robust" variance estimate.

Greetings R Help Group, How does one effect a multiphasic logistic growth model with 4 phases (e.g. Koops 1986; Weigel, Craig, Bidwell and Bates 1992; Grossman and Koops 2003) with R. Before writing to the group, the R help archives were searched, the web was searched with Google, Venables and Ripley 2002 was consulted, Pinheiro and Bates 2000 was consulted, Bates and Watts 2007 was bought and

Hi All, I am in the middle of doing an analysis of a Case-Cohort design. I had three questions about the analysis: a) Does any one know of some public code for developing the patient risk sets (indexed by failure time) or is there a better way to organize the data? b) I was planning to use the Barlow weighting method. Has this or any other weighting method (Prentice, Self-Prentice) been

I am designing an interlaboratory validation study for a presence/absence alternative method test kit vs. a presence/absence reference method test kit. There will be 10 laboratories conducting tests using both methods. In each laboratory, there will be 5 specimens tested, each of the 5 specimens twice by both methods (alternative, standard). The total number of data are 10 x 5 x 4 = 200.

Dear R-list, I think it's really a newbie question but ... I try to model age-period-cohort models with polynoms in each effect. I have for each level of age and period some cases -k- and persons-years -py-. Models are A_xP_y: log(k_age,period/py_age,period)=f(polynom(x),age)+f(polynom(y),period). For exemple I try to adjust an A2P3 :

[Corrected the model formula to include "method".] I am designing an interlaboratory validation study for a presence/absence alternative method test kit vs. a presence/absence reference method test kit. There will be 10 laboratories conducting tests using both methods. In each laboratory, there will be 5 specimens tested, each of the 5 specimens twice by both methods (alternative,

Hi R Users, I wish to estimate if there is a trend in my relative risk obtained by coxph. The best i've found is a method from Greenland and Longnecker ( Am J Epidemiology 1992 vol 135 (11) - p 1301-9 ). But all I have is my relative risk and their std error. Is there a command in R that can do this ? If there is someone with a better method ? Thanking you in advance, I look forward your

Dear R users: Analysis of the impact of a time-dependent covariate (GVHD or use of steroid after bone marrow transplantation) on two competing endpoints (invasive fungal infection and death) is frequently encountered in the setting of BMT data. Coxph package can be used as the following: for the analysis of GVHD: > gvhd -> coxph(Surv(start,stop,status = =1) ~ GVHD, data=bmt.data)

Dear all, I have a question about time-dependent covariates in a coxph model. Specifically I am wondering whether it is possible to give more recent events a higher weight when constructing time-dependent covariates. Assume I have a sample of cancer patients and I would like to predict whether the number of treatments a patient received has an impact on survival time. For each patient in my

Dear list: I am attempting to use what I thought would be a pretty straightforward practical application of Cox regression. I figure users of the survival package must have come across this problem before, so I would like to ask you how you dealt with it. I have set up an illustrative example and included it at the end of this post. I took a sample of 100 data points from each of two populations

Hi everyone, I encountered a problem using the coxph function for the conditional logistic regression. I am trying to do some simulations and I really don’t understand a mistake which happened maybe only 1 time among more than 1,000 simulations. What appeared on the screen is the following: Error in fitter(X,Y,strats,offset,init,control,weights=weights,: NA/NaN/Inf in a foreign function (arg