Re: [R] Survival analysis

cpolwart wrote: > the event can only happen once > 1. Yes, I'm not interested in repeat events. 2. I just had an interest in learning the code for survival analysis in case there are: event, left censored (not left truncating) and right censored, nothing more! But I no longer want to burden anyone

Re: [R] Survival analysis

On 2020-04-26 10:48, Medic wrote: Very grateful for the all comments! My data contains: • left censored • right censored • events (interval censored does not contain!) (P.S. I understood, that the code with "type = 'left'" is not suitable, because is ONLY for left-censored.) I wanted to get

Re: [R] Survival analysis

Very grateful for the all comments! My data contains: • left censored • right censored • events (interval censored does not contain!) (P.S. I understood, that the code with "type = 'left'" is not suitable, because is ONLY for left-censored.) I wanted to get the appropriate code for my so mix

Re: [R] Survival analysis

Dear dr Medic, Den 2020-04-17 kl. 23:03, skrev Medic: On 2020-04-17 20:06, Medic wrote: I can't understand how to do a survival analysis (?Surv ()) when some event occurred before the start of observation (left censored). If I understand correctly, there are two methods. I chose a method with:

Re: [R] Survival analysis

On 2020-04-17 20:06, Medic wrote: > I can't understand how to do a survival analysis (?Surv ()) when some > event occurred before the start of observation (left censored). If I > understand correctly, there are two methods. I chose a method with: 1) > time from the start of treatment to the event

Re: [R] Survival analysis

On 2020-04-17 20:06, Medic wrote: I can't understand how to do a survival analysis (?Surv ()) when some event occurred before the start of observation (left censored). If I understand correctly, there are two methods. I chose a method with: 1) time from the start of treatment to the event and 2)

[R] Survival analysis

I can't understand how to do a survival analysis (?Surv ()) when some event occurred before the start of observation (left censored). If I understand correctly, there are two methods. I chose a method with: 1) time from the start of treatment to the event and 2) the indicator of the event. I did

Re: [R] survival analysis question

Thank You,Eric. I run this code without id="id" and it worked! Eric Berger :    Medic via  R - help  < r - help @ r -project.org > wrote: addicts.cp=survSplit(addicts, cut=addicts$survt[addicts$status==1], > end="survt", event="status",start="start", id="id") >ERROR in survSplit(addicts,

Re: [R] survival analysis question

You need to read the Help page for the function survSplit ?survSplit states that the id argument is a "character string with the name of new id variable to create (optional). This can be useful if the data set does not already contain an identifier" The addicts data.frame has as its first

[R] survival analysis question

When I run the code from the book Kleinbaum "Survival analysis" (7. Running an extended cox model. Page 646) I got an ERROR. What do you think is the reason? I attach a file with few lines of dataset "addicts-dput.r". > library(cmprsk) > addicts = read.csv ("addicts.csv")     id clinic status

Re: [R] survival analysis - predict function

> On Oct 16, 2017, at 8:28 AM, Meghna Govil wrote: > > Hi > > I'm trying to predict the values for a survreg object called > loglogistic_na. Here is the definition of loglogistic_na and following that > the syntax used for the predict function. But upon execution I

[R] survival analysis - predict function

> Hi > > I'm trying to predict the values for a survreg object called loglogistic_na. > Here is the definition of loglogistic_na and following that the syntax used > for the predict function. But upon execution I don't get any output. Not sure > what I'm doing wrong: > > loglogistic_na <-

[R] survival analysis - predict function

Hi I'm trying to predict the values for a survreg object called loglogistic_na. Here is the definition of loglogistic_na and following that the syntax used for the predict function. But upon execution I don't get any output. Not sure what I'm doing wrong: loglogistic_na <-

[R] Survival analysis with interval censored data

Hi! Does anyone know about survival analysis using interval censored data and the intcox package? I fed different ant colonies with different food (called treatment) and I measured every 2 days the death of ants. I would like to see if the treatment can explain a different death of individuals.

Re: [R] Survival analysis: ERROR: Time and status are different lengths

I expect that reading the result of print(fit.weib) will answer your question. If there were any missing values in the data set, then the fit.weib$linear.predictors will be shorter than the original data set, and the printout will have a note about "...deleted due to missing". The simplest

Re: [R] Survival analysis: ERROR: Time and status are different lengths

Hi Terry, I already suspected it had something to do with missing values in one of the covariates. I couldn't get the na.action="na.exclude" to work (perhaps this is because I am relatively unexperienced with R), but I managed to solve the problem by using the following command with

[R] Survival analysis: ERROR: Time and status are different lengths

Hi, I am fitting an AFT model assuming a Weibull distribution and I would like to check the residuals compared to the Kaplan Meier residuals, but when I try to create the Kaplan Meier residuals I get an error: Time and status are different lengths. I am using the following script: # Fitting the

Re: [R] Survival Analysis and Predict time-to-death

On 2015-08-18 01:44, David Winsemius wrote: On Aug 17, 2015, at 1:51 PM, David Winsemius wrote: On Aug 17, 2015, at 12:10 PM, survivalUser wrote: Dear All, I would like to build a model, based on survival analysis on some data, that is able to predict the /*expected time until death*/

Re: [R] Survival Analysis and Predict time-to-death

It depends on several factors. You need answers to all these questions: How many events occurred, ... and was the period of observation long enough to cover a significant fraction of the life expectancy, …. and is there external evidence or theory that will help establish that this process

Re: [R] Survival analysis and predict time-to-death

I read this list a day late as a digest so my answers are rarely the first. (Which is nice as David W answers most of the survival questions for me!) What you are asking is reasonable, and in fact is common practice in the realm of industrial reliability, e.g., Meeker and Escobar, Statistical

Re: [R] Survival Analysis and Predict time-to-death

On Aug 17, 2015, at 3:39 PM, Bert Gunter wrote: David: I may have misunderstood you here, specifically: As such I would ask if you really wanted to use a parametric survival model in the first place? The K-M curve is , of course, a **non-parametric** fit, and that is why there can

Re: [R] Survival Analysis and Predict time-to-death

On Aug 17, 2015, at 1:51 PM, David Winsemius wrote: On Aug 17, 2015, at 12:10 PM, survivalUser wrote: Dear All, I would like to build a model, based on survival analysis on some data, that is able to predict the /*expected time until death*/ for a new data instance. Are you sure

Re: [R] Survival Analysis and Predict time-to-death

Ooops. I meant to drop that other message but hit the send icon instead. On Aug 17, 2015, at 3:39 PM, Bert Gunter wrote: David: I may have misunderstood you here, specifically: As such I would ask if you really wanted to use a parametric survival model in the first place? The K-M

Re: [R] Survival Analysis and Predict time-to-death

David: I may have misunderstood you here, specifically: As such I would ask if you really wanted to use a parametric survival model in the first place? The K-M curve is , of course, a **non-parametric** fit, and that is why there can be no mean survival time unless the last point is a death.

Re: [R] Survival Analysis and Predict time-to-death

Thank you David for your answer. Some follow-up questions: - So, do you think that try to estimate the life expectancy would be risky and probably not justifiable? Is there some sort of 'confidence' that the model could give me for a prediction? - type=response - I found it here:

[R] Survival Analysis and Predict time-to-death

Dear All, I would like to build a model, based on survival analysis on some data, that is able to predict the /*expected time until death*/ for a new data instance. Data For each individual in the population I have the, for each unit of time, the status information and several continuous

Re: [R] Survival Analysis and Predict time-to-death

On Aug 17, 2015, at 12:10 PM, survivalUser wrote: Dear All, I would like to build a model, based on survival analysis on some data, that is able to predict the /*expected time until death*/ for a new data instance. Are you sure you want to use life expectancy as the outcome? In order to

Re: [R] Survival Analysis with an Historical Control

code is very interesting. Especially the parametric part. Nice to get an actual p-value for the test. Thanks, Paul On Mon, 7/21/14, Andrews, Chris chri...@med.umich.edu wrote: Subject: RE: [R] Survival Analysis with an Historical Control Cc: r-help

Re: [R] Survival Analysis with an Historical Control

: Thursday, July 10, 2014 8:59 AM To: Andrews, Chris Cc: r-help@r-project.org Subject: RE: [R] Survival Analysis with an Historical Control Hi Chris, Thanks for pointing out the use of View page source. Very helpful to know. Do you happen to know anything about how to perform the analysis itself

Re: [R] Survival Analysis with an Historical Control

You are asking for a one sample test. Using your own data: connection - textConnection( GD2 1 8 12 GD2 3 -12 10 GD2 6 -52 7 GD2 7 28 10 GD2 8 44 6 GD2 10 14 8 GD2 12 3 8 GD2 14 -52 9 GD2 15 35 11 GD2 18 6 13 GD2 20 12 7 GD2 23 -7 13 GD2 24 -52 9 GD2 26 -52 12

Re: [R] Survival Analysis with an Historical Control

Hi Dr. Therneau, Thanks for your response. This is very helpful. My historical control value is 16 weeks. I've been having some trouble though determining how this value was obtained. Are you able to indicate how people normally go about determining a value for the historical control? Or do

Re: [R] Survival Analysis with an Historical Control

On Wed, 7/9/14, Andrews, Chris chri...@med.umich.edu wrote: Subject: RE: [R] Survival Analysis with an Historical Control r-project.org Received: Wednesday, July 9, 2014, 11:26 AM The code is actually available at the websites you provide.  Try View

Re: [R] Survival Analysis with an Historical Control

] Sent: Tuesday, July 08, 2014 12:00 PM To: r-help@r-project.org Subject: [R] Survival Analysis with an Historical Control Hello All, I'm trying to figure out how to perform a survival analysis with an historical control. I've spent some time looking online and in my boooks but haven't found much

[R] Survival Analysis with an Historical Control

Hello All, I'm trying to figure out how to perform a survival analysis with an historical control. I've spent some time looking online and in my boooks but haven't found much showing how to do this. Was wondering if there is a R package that can do it, or if there are resources somewhere that

[R] Survival analysis

Dear R users, how I can implement Breslow and Tarone-Ware tests for survival analysis? Also, is there any way I can estimate and plot the hazard function,along the lines of the survival function in Survival Package? (The package muhaz seems that does not do what it promises, except if I could not

Re: [R] Survival analysis

On Jan 28, 2014, at 7:58 AM, Endy BlackEndy wrote: Dear R users, how I can implement Breslow and Tarone-Ware tests for survival analysis? Tests ... of what? Perhaps you should learn to search: install.packages('sos') library(sos) findFn(Tarone-Ware) The 'comp' function in {survMisc}

Re: [R] Survival analysis

On Jan 28, 2014, at 4:19 PM, Dennis Murphy wrote: Hi David: Do you meant [sic] the (cumulative) hazard function that is 1 minus the survival function? Um, 1 - S(t) = F(t), the cumulative *distribution function* of the random variable T. The cumulative hazard function is -ln S(t) and

Re: [R] Survival analysis with truncated data

I think that your data is censored, not truncated. For a fault introduced 1/2005 and erased 2/2006, duration = 13 months For a fault introduced 4/2010 and still in existence at the last observation 12/2010, duration 8 months. For a fault introduced before 2004, erased 3/2005, in a machine

Re: [R] Survival analysis with truncated data

Hi, Thanks for your response. On Thu, Nov 14, 2013 at 4:44 PM, Terry Therneau thern...@mayo.edu wrote: I think that your data is censored, not truncated. For a fault introduced 1/2005 and erased 2/2006, duration = 13 months For a fault introduced 4/2010 and still in existence at the last

[R] Survival analysis with truncated data.

Hi, I would like to know how to handle truncated data. My intend is to have the survival curve of a software fault in order to have some information about fault lifespan. I have some observations of a software system between 2004 and 2010. The system was first released in 1994. The event

[R] survival analysis simulation question

Hi, I am trying to simulate a regression on survival data under a few conditions: 1. Under different error distributions 2. Have the error term be dependent on the covariates But I'm not sure how to specify either conditions. I am using the Design package to perform the survival analysis using

Re: [R] survival analysis simulation question

On Thu, May 10, 2012 at 7:41 PM, Grace Ma grace.yanfe...@gmail.com wrote: Hi, I am trying to simulate a regression on survival data under a few conditions: 1. Under different error distributions 2. Have the error term be dependent on the covariates But I'm not sure how to specify either

Re: [R] survival analysis simulation question

Hi Grace, I seem to have sent an empty draft before. Anyway, something like this might be an approach (untested): require(rms) set.seed(10) dat - data.frame( age = rnorm(500, 40, 10), race = factor(sample.int(2,500,TRUE), labels = c(a, b))) X - model.matrix(~ age + race, data = dat) b -

Re: [R] survival analysis simulation question

I forgot to mention, the Design package is deprecated (which suggest your version of R is rather dated, current is 2.15). The rms package replaces Design. On Thu, May 10, 2012 at 10:23 PM, Joshua Wiley jwiley.ps...@gmail.com wrote: Hi Grace, I seem to have sent an empty draft before.  Anyway,

Re: [R] Test-Predict R survival analysis

On 04/18/2012 05:00 AM, r-help-requ...@r-project.org wrote: Hi, I'm trying to use the R Survival analysis on a windows 7 system. The input data format is described at the end of this mail. 1/ I tried to perform a survival analysis including stratified variables using the following formula

[R] Survival analysis with events at t=0

Dear All Does any one know if the following survival analysis exists, and if so, is it available in R? I am trying to parametrically model survival where some events happen at time = 0. I am particularly interested in generating the 95% confidence interval around the survival function over

[R] Test-Predict R survival analysis

Hi, I'm trying to use the R Survival analysis on a windows 7 system. The input data format is described at the end of this mail. 1/ I tried to perform a survival analysis including stratified variables using the following formula. cox.xtab_miR=coxph(Surv(time, status) ~ miR + strata(sex,nbligne

[R] Survival analysis and comparing survival curves

Hei, I have a one simple question which does not seem to be that simple as I cannot find any solution/answer: Is it possible to compare multiple survival curves in R with survdiff-function when there is interaction term involved in predictor variables (and this interaction is significant)?

Re: [R] Survival analysis and comparing survival curves

DEAR R-girl: On Thu, Feb 23, 2012 at 8:12 AM, R-girl jhovi...@gmail.com wrote: Hei, I have a one simple question which does not seem to be that simple as I cannot find any solution/answer: Is it possible to compare multiple survival curves in R with survdiff-function when there is

Re: [R] Survival analysis and comparing survival curves

On Feb 23, 2012, at 11:12 AM, R-girl wrote: Hei, I have a one simple question which does not seem to be that simple as I cannot find any solution/answer: Is it possible to compare multiple survival curves in R with survdiff-function when there is interaction term involved in predictor

Re: [R] Survival analysis

On Sun, 2011-10-23 at 12:00 +0200, r-help-requ...@r-project.org wrote: The results by the survfit routine do not agree with the results of these formulae as obtained by SAS. The next question should be is SAS correct. The answer in this case is no. For survival data the mean

Re: [R] Survival analysis

Hello Terri, Thank you very much. This is the answer I needed. Could you also tell me how I can calculate 25 and 50% quantiles in R? I can only get median as far as I know. Cem Cem Girit   -Original Message- From: Terry Therneau [mailto:thern...@mayo.edu] Sent: Monday,

[R] Survival analysis

Hello, I need some results from the survival analysis of my data that I do not know whether exist in Survival Package or how to obtain if they do: 1. The Mean survival time 2. The standard error of the mean 3. Point and 95% Lower Upper Confidence

Re: [R] Survival analysis

Hi, On Thu, Oct 20, 2011 at 2:04 PM, Cem Girit gi...@biopticon.com wrote: Hello,                I need some results from the survival analysis of my data that I do not know whether exist in Survival Package or how to obtain if they do: 1.       The Mean survival time 2.       The

Re: [R] Survival analysis

Plainsboro, NJ 08536 Tel: (609) 275 0321 Email:gi...@comcast.net -Original Message- From: Sarah Goslee [mailto:sarah.gos...@gmail.com] Sent: Thursday, October 20, 2011 2:20 PM To: Cem Girit Cc: r-help@r-project.org Subject: Re: [R] Survival analysis Hi, On Thu, Oct 20, 2011

Re: [R] Survival analysis

On Oct 20, 2011, at 5:05 PM, Sarah Goslee wrote: Hi, Please send your information to the r-help list, not just to me, but do note that the list is plain-text only. But surely all you are looking for is: dt- c

Re: [R] survival analysis: interval censored data

You have still not given me enough information to reproduce your problem. Why doesn't it include all years? I have no way of knowing, since we have no data. --- begin included message -- halo david when I use type= 'interval' Call: survfit(formula = Surv(ingreso, fecha, estado, type =

Re: [R] survival analysis: interval censored data

hallo terry: I attached araceae data set, when I use this: surara-survfit(Surv(time,time2,event)~categoria) Call: survfit(formula = Surv(time, time2, event) ~ categoria)     records n.max n.start events median 0.95LCL 0.95UCL categoria=C  94    63   0 21 NA  NA  

Re: [R] survival analysis: interval censored data

On Sep 28, 2011, at 10:56 AM, Ruth Arias wrote: hallo terry: I attached araceae data set, The usual survival analysis via the Kaplan-Meier method only make estimates at the time of events. When you tabulate your data, you see that there were no events for the missing (starting) time

Re: [R] survival analysis: interval censored data

David, Thanks for taking time to answer this. When there are interval censored data, computation of the MLE first finds a minimal number of time points such that every interval with a death contains one of those points. Those are the points at which the final curve can have a jump. The

Re: [R] survival analysis: interval censored data

Thanks for taking time to answer this De: Terry Therneau thern...@mayo.edu Para: David Winsemius dwinsem...@comcast.net .org Enviado: miércoles 28 de septiembre de 2011 23:03 Asunto: Re: [R] survival analysis: interval censored data David,   Thanks

Re: [R] survival analysis: interval censored data

-project.org Enviado: martes 27 de septiembre de 2011 7:06 Asunto: Re: [R] survival analysis: interval censored data Please adhere to the posting guide (i.e., provide a sample of self contained code and provide the error message). And what does but it is not working mean? Is there an error code

[R] survival analysis: interval censored data

hello: my data looks like: time1  time2   event  catagoria 2004    2006        1            C 2004    2005        0            C 2005    2010        1            E 2007    2009        1            C 2006    2007        0            E 2008    2010        0            C 2008    2010       

Re: [R] survival analysis: interval censored data

Please adhere to the posting guide (i.e., provide a sample of self contained code and provide the error message). And what does but it is not working mean? Is there an error code? rueu wrote: hello: my data looks like: time1  time2   event  catagoria 2004    2006        1            C

[R] Survival Analysis for soccer scoring process

6.4.1 Estimation of fixed effects Heterogeneous team ability is a possible explanation for the result in Section 6.3. That result simply indicates that the more goals a team scores, the higher the probability that it will score more. However, teams that can score more goals also indicate teams

[R] survival analysis of EEG data

Hi everybody, I'm fairly new to survival analysis with R and have some questions how to apply and interpret the coxph and related functions: I have time-dependent covariates with several measurements per subject with constant delta t. The covariates change in each time step. I fitted the

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

2011/7/21 Abdullah OUESLATI abouesl...@gmail.com: quote author=Göran Broström [...] I do not understand why you expect to get comparable results with SAS discrete and coxph exact. They are two different approaches to handling ties (as Terry explained; of course, some comparability should be

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

quote author=Göran Broström [...] I do not understand why you expect to get comparable results with SAS discrete and coxph exact. They are two different approaches to handling ties (as Terry explained; of course, some comparability should be expected in normal cases). [...] /quote I didn't know

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

Let me expand a bit on Thomas's answer. Looking more closely at your data set you have the following: death time group 0group 1 1.5 0/413/13 3 0/4 5/5 8 4/4 0 At time 1.5 group 1 had 13 deaths out of

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

://r.789695.n4.nabble.com/comparing-SAS-and-R-survival-analysis-with-time-dependent-covariates-tp874438p3680340.html Sent from the R help mailing list archive at Nabble.com. __ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

for the memory configuration of your computer. -- View this message in context: http://r.789695.n4.nabble.com/comparing-SAS-and-R-survival-analysis-with-time-dependent-covariates-tp874438p3680340.html Sent from the R help mailing list archive at Nabble.com

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

that the results obtained by SAS are reliable in such cases ? Thank you for your answer. -- View this message in context: http://r.789695.n4.nabble.com/comparing-SAS-and-R-survival-analysis-with-time-dependent-covariates-tp874438p3678763.html Sent from the R help mailing list archive at Nabble.com

Re: [R] comparing SAS and R survival analysis with time-dependent covariates

On Wed, Jul 20, 2011 at 5:42 AM, AO_Statistics abouesl...@gmail.com wrote: Terry Therneau-2 wrote: This query of why do SAS and S give different answers for Cox models comes up every so often.  The two most common reasons are that       a. they are using different options for the ties      

Re: [R] Survival Analysis

On Jul 18, 2011, at 10:10 AM, Kishor Tappita wrote: Dear David, Thank you for your reply. I realized that the summary function can help me in finding the the order of the curves. The 0.95UCL (95% upper confidence level) column in particular seems to follow the same pattern as the

Re: [R] Survival Analysis

Dear David, Thank you for your reply. I realized that the summary function can help me in finding the the order of the curves. The 0.95UCL (95% upper confidence level) column in particular seems to follow the same pattern as the curves on the plot. I am new to survival analysis, so please

Re: [R] Survival Analysis

On Jul 18, 2011, at 10:42 AM, Kishor Tappita wrote: Ok David, Thanks for clearing my misconception. Then could you please suggest me how I could get the KM estimate for a time point. I remember reading the formula for calculating the KM. Do, I have to write a method to compute the KM

Re: [R] Survival Analysis

Ok David, Thanks for clearing my misconception. Then could you please suggest me how I could get the KM estimate for a time point. I remember reading the formula for calculating the KM. Do, I have to write a method to compute the KM estimate or will the survival package provide it for me? Thank

Re: [R] Survival Analysis

Thanks a lot. I used survfit to generate KM plots but I will try to figure out to find the corresponding returned value for KM estimate. Thank you for your invaluable help. On Mon, Jul 18, 2011 at 8:28 PM, David Winsemius dwinsem...@comcast.netwrote: On Jul 18, 2011, at 10:42 AM, Kishor

[R] Survival Analysis

Dear List, I used survival package of R and was able to generate KM plots. Now I need help in finding the top curve in a non-visualization way. I mean to say that I would like to know the order of curves through any existing methods rather than looking at the KM plots. I need this information as

Re: [R] Survival Analysis

On Jul 17, 2011, at 11:27 AM, Kishor Tappita wrote: Dear List, I used survival package of R and was able to generate KM plots. Now I need help in finding the top curve in a non-visualization way. I mean to say that I would like to know the order of curves through any existing methods

[R] Survival Analysis

Hello, I have few questions about recurring events. I would greatly appreciate it if anyone can assist me. I have data that consist of approx 1,100 Consecutive patients released from hospital after first Myocardial infarction (MI). They were followed for 13 years. Recurrent MI and unstable

Re: [R] Survival analysis: same subject with multiple treatments

---Begin inclusion -- I need some help to figure out what is the proper model in survival analysis for my data. Subjects were randomized to 3 treatments in trial 1, some of them experience the event during the trial; After period of time those subjects were randomized to 3 treatments again in

Re: [R] Survival analysis: same subject with multiple treatments and experience multiple events

Date: Fri, 22 Apr 2011 10:00:31 -0400 From: littleduc...@gmail.com To: r-help@r-project.org Subject: [R] Survival analysis: same subject with multiple treatments and experience multiple events Hi there, I need some help to figure out what

[R] Survival analysis: same subject with multiple treatments and experience multiple events

Hi there, I need some help to figure out what is the proper model in survival analysis for my data. Subjects were randomized to 3 treatments in trial 1, some of them experience the event during the trial; After period of time those subjects were randomized to 3 treatments again in trial 2, but

[R] survival analysis microarray expression data

Hi there I want to test the expression of a subset of genes for correlation with patient survival. I found out that the coxph function is appropriate for doing this since it works with continuous variables such as Affy mRNA expression values. I applied the following code: cp -

Re: [R] Survival Analysis Daily Time-Varying Covariate....

Help! I am unsure if I can analyze data from the following experiment. Fish were placed in a tank at (t=0) Measurements of Carbon Dioxide were taken each day for 120 days (t=0,...120) A few fish were then randomly pulled out of the tank at different days, killed and examined for the presence of

[R] Survival Analysis Daily Time-Varying Covariate but Event Time Unknown

Help! I am unsure if I can analyze data from the following experiment. Fish were placed in a tank at (t=0) Measurements of Carbon Dioxide were taken each day for 120 days (t=0,...120) A few fish were then randomly pulled out of the tank at different days, killed and examined for the presence of

Re: [R] Survival Analysis Daily Time-Varying Covariate but Event Time Unknown

On Sep 16, 2010, at 12:14 PM, smm7aa wrote: Help! I am unsure if I can analyze data from the following experiment. Fish were placed in a tank at (t=0) Measurements of Carbon Dioxide were taken each day for 120 days (t=0,...120) A few fish were then randomly pulled out of the tank at

Re: [R] Survival Analysis Daily Time-Varying Covariate but Event Time Unknown

On Sep 16, 2010, at 4:43 PM, David Winsemius wrote: On Sep 16, 2010, at 12:14 PM, smm7aa wrote: Help! I am unsure if I can analyze data from the following experiment. Fish were placed in a tank at (t=0) Measurements of Carbon Dioxide were taken each day for 120 days (t=0,...120) A few

Re: [R] Survival analysis MLE gives NA or enormous standard errors

Hi Charles, On Fri, 2010-07-23 at 14:40 -0700, Charles C. Berry wrote: On Fri, 23 Jul 2010, Christopher David Desjardins wrote: Sorry. I should have included some data. I've attached a subset of my data (50/192) cases in a Rdata file and have pasted it below. Running anova I get the

Re: [R] Survival analysis MLE gives NA or enormous standard errors

On Tue, 27 Jul 2010, Christopher David Desjardins wrote: Hi Charles, On Fri, 2010-07-23 at 14:40 -0700, Charles C. Berry wrote: On Fri, 23 Jul 2010, Christopher David Desjardins wrote: Sorry. I should have included some data. I've attached a subset of my data (50/192) cases in a Rdata file

[R] Survival analysis MLE gives NA or enormous standard errors

Hi, I am trying to fit the following model: sr.reg.s4.nore - survreg(Surv(age_sym4,sym4), as.factor(lifedxm), data=bip.surv) Where age_sym4 is the age that a subject develops clinical thought problems; sym4 is whether they develop clinical thoughts problems (0 or 1); and lifedxm is

Re: [R] Survival analysis MLE gives NA or enormous standard errors

On Fri, 23 Jul 2010, Christopher David Desjardins wrote: Hi, I am trying to fit the following model: sr.reg.s4.nore - survreg(Surv(age_sym4,sym4), as.factor(lifedxm), data=bip.surv) Next time include a reproducible example. i.e. something we can run. Now, Google Hauck Donner Effect to

Re: [R] Survival analysis MLE gives NA or enormous standard errors

Sorry. I should have included some data. I've attached a subset of my data (50/192) cases in a Rdata file and have pasted it below. Running anova I get the following: anova(sr.reg.s4.nore) Df Deviance Resid. Df-2*LL P(|Chi|) NULL NA NA45

Re: [R] Survival analysis MLE gives NA or enormous standard errors

On Fri, 23 Jul 2010, Christopher David Desjardins wrote: Sorry. I should have included some data. I've attached a subset of my data (50/192) cases in a Rdata file and have pasted it below. Running anova I get the following: anova(sr.reg.s4.nore) Df Deviance Resid. Df

Re: [R] Survival analysis extrapolation

Dear Terry, Thanks so much for your help; I'm a bit of an R novice at the moment (as you can probably tell from my failure to use the data argument!) so any help is most welcome. I'm hoping to use this model to generate transition probabilities for a Markov model and, as such, I was wondering

Re: [R] Survival analysis extrapolation

A few suggestions 1. Use the data argument wfit - survreg(Surv(Time, Status) ~ Treatment, data=survdata) summary(wfit) 2. Use the predict function to look at your survival curve. This avoids any parameter change mistakes. It also works for any distribution. pp - 0:60/100 wsurv -

[R] Survival analysis extrapolation

Dear all, I'm trying to fit a curve to some 1 year failure-time data, so that I can extrapolate and predict failure rates up to 3 years. The data is in the general form: Treatment Time Status Treatment A28 0

[R] Survival analysis

Dear all I have a dataset examining the probability of a population surviving (calculated from a logistic regression) of a species over a 200yr period. The predictor variables are either continuous but non-normal (e.g. temperature, oxygen) or categorical (e.g. channelisation), unfortunately I

Re: [R] Survival analysis

On Feb 17, 2010, at 1:54 PM, FishR wrote: Dear all I have a dataset examining the probability of a population surviving (calculated from a logistic regression) of a species over a 200yr period. The predictor variables are either continuous but non-normal (e.g. temperature, oxygen) or

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