search for: infarcted

Hi, I have two different imaging modalities (for the identification of areas of infarcted myocardium) that I need to compare regarding agreement and consistency. However, I don't think that methods like Cohen's Kappa, PCC, Bland-Altmann or ICC are sufficient here as there is not just a pairwise but also a spatial relationship between measured data points. For example if the resu...

Hello everyone, I am ploting a groupeddata object with formula: formula(mydatausegroup) BF ~ HO | ID/Infar/Day Using this command: plot(na.omit(mydatausegroup), displayLevel=2,layout=c(10,2),aspect=2) This trellis plot does almost what I want and produces a 10x2 trellis plot, each panel is labeled as ID/Infar where infarct is either 1 or 0. And in each panel, it plots BF vs HO for each Day.

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

Dear all, I am using the publically available GustoW dataset. The exact version I am using is available here: https://drive.google.com/open?id=0B4oZ2TQA0PAoUm85UzBFNjZ0Ulk I would like to produce a nomogram for 5 covariates - AGE, HYP, KILLIP, HRT and ANT. I have successfully fitted a logistic regression model using the "glm" function as shown below. library(rms) gusto <-

> On Sep 14, 2017, at 12:30 AM, Bonnett, Laura <L.J.Bonnett at liverpool.ac.uk> wrote: > > Dear all, > > I am using the publically available GustoW dataset. The exact version I am using is available here: https://drive.google.com/open?id=0B4oZ2TQA0PAoUm85UzBFNjZ0Ulk > > I would like to produce a nomogram for 5 covariates - AGE, HYP, KILLIP, HRT and ANT. I have

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

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;

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=placebo and 2=drug) Sex,

Fixed 'maxiter' in the help file. Thanks. Please give the original source of that dataset. That dataset is a tiny sample of GUSTO-I and not large enough to fit this model very reliably. A nomogram using the full dataset (not publicly available to my knowledge) is already available in http://biostat.mc.vanderbilt.edu/tmp/bbr.pdf Use lrm, not lrm.fit for this. Adding maxit=20 will

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

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

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

Dear Xen Users, I have _partial_ (that is, less than 100%) success following Jean David Techer''s Xen 4.2-unstable VGA Passthrough Documentation. In both Windows 8 Consumer Preview HVM and Windows XP Home Edition HVM, I get yellow exclamation mark besides NVIDIA Geforce 8400 GS in Device Manager. NVIDIA Geforce 8400 GS in Device Manager reports: 1) Windows has stopped this device

Dear Xen Users, I have _partial_ (that is, less than 100%) success following Jean David Techer''s Xen 4.2-unstable VGA Passthrough Documentation. In both Windows 8 Consumer Preview HVM and Windows XP Home Edition HVM, I get yellow exclamation mark besides NVIDIA Geforce 8400 GS in Device Manager. NVIDIA Geforce 8400 GS in Device Manager reports: 1) Windows has stopped this device