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Hello, I have a cohort with approx 1,200 patients at the ages of 30-65 that had their first myocardial infarction during 1992: · They were in a follow up until 2005. · About 400 of them died during this period of time (right censored) · Each one of them had up to 4 mi recurrent events. I am using the semi-parametric model in order to assess the relationship of predictors...

Hello everybody, in the past months I have developed a model to predict the mortality rate of Acute Myocardial Infarction Patients. My evaluation was mainly based on ROC Curves etc. I have now been asked to calculate the R-Square of my model, another existing model in regards to the actual mortality rate. So far I have only found a function calculating a regression, and then the R-Square of the calculated...

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 angina pectoris (UAP) leading to hospitalization were recorded (within-subject range: 0-4 for recurrent MI; 0-19 for UAP). Socio demographic and clinical data were obtained at study entry. I want to fit Semiparametric regr...

Hi , I have a data set with recurrence time (up to four) of myocardial infarction (MI). Part of the file is showing below: Num1 Trt Sex Time T1 T2 T3 T4 1011 1 1 9 1211 0 1 59 3020 1 2 14 3 1245 0 1 18 12 16 3069 1 2 26 6 12 13 2051 0 1 53 3 15 46 51 The data consist of the following eight variables: Num1 , patient number Trt, treatment group (1=place...

...ial relationship between measured data points. For example if the results of the two imaging modalities are slightly misaligned their agreement might be still much better than the mentioned tests might indicate (at least from a practical point of view). On the other hand the number of non-infarcted myocardial segments often heavily outweighs the number of infarcted segments which seems to introduce a bias towards better agreement in most examinations. Here is an example data set, where I've calculated the ICC. What would be the "correct" way to assess agreement and consistency here? # mo...

Dear Experts, I am trying to do a time-stratified case-crossover analysis on air pollution data and number of myocardial infarctions. In order to avoid model selection bias, I started with a simple simulation. I'm still not sure if my simulation is right. But the results I get from the "ts-case-crossover" are much more variable than those from a glm. Is this: a. Due to the simple relation of l...

Dear Experts, I am trying to do a time-stratified case-crossover analysis on air pollution data and number of myocardial infarctions. In order to avoid model selection bias, I started with a simple simulation. I'm still not sure if my simulation is right. But the results I get from the "ts-case-crossover" are much more variable than those from a glm. Is this: a. Due to the simple relation of log-rate...

We have two time series: the first is a series of weekly counts of isolates of RSV (respiratory syncytial virus) by pathology laboratories, and the second is a series of weekly counts of cases of bronchiolitis in young children presenting to hospital emergency departments. Bronchiolitis in young children is usually caused by RSV infection, and simple visual inspection reveals a very close

Hi, I'm new to R and using it for Cox survival analysis. Thanks to this great forum I learned how to compute the HR with its confidence interval. My question would be: Is there any way to get the p-value for a hazard ratio in addition to the confidence interval? Thanks, Thierry -- Thierry Panje Visiting Student Researcher Department of Psychology Stanford