similar to: What''s the best way to select one in a big list?

Hello everyone, I have a data set that contains characteristics of 25,000 patients of 92 different hospitals. I have run a regression to capture the probability these patients will have a complication after a certain operation. Now, I actually want to predict the probability per patient, using the outcome of the regression, but I just certain patients involved in the prediction. So, I want to use

Hi, Could someone help with coding this in R? I need to select one row per patient i in clinic j. The data is organized similar to that shown below. Two columns - patient i in column j identify each unique patient. There are two columns on outcome. Some patients have multiple rows with each row representing one visit, coded for in the column, visit. Some patients have just one row indicating

I have what I *think* should be a simple problem in R, and hope someone might be able to help me. I'm working with cancer survival data, and would like to calculate adjusted survival figures based on the age of the patient and the tumour classification. A friendly statistician told me I should use Cox proportional hazards to do this, and I've made some progress with using the

Hi dear R community, I have up to 12 measures of a protein for each of 6 patients, taken every two or three days. The pattern of the protein looks periodic, but the height of the peaks is highly variable. It's something like this: patient <- data.frame( day = c(1, 3, 5, 8, 10, 12, 15, 17, 19, 22, 24, 26), protein = c(5, 3, 10, 7, 2, 8, 25, 12, 7, 20, 10, 5) ) plot(patient$day,

Hi, i have an model, which i want to show edit and update in a dialog via ajax. What i do at the moment: To open the Modal and render the partial, i send an ajax request to controller#show with ujs this is the link: <a class="person-dialog" data-remote="true" data-type="script" href="/en/people/32" onclick="return false">Fidel

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

I'm working with a nested model (mixed). I have four factors: Patients, Tissue, sex, and tissue_stage. Totally I have 10 patients, for each patient, there are 2 tissues (Cancer vs. Normal). I think Tissue and sex are fixed. Patient is nested in sex,Tissue is nested in patient, and tissue_stage is nested in Tissue. I tried aov and lme as the following, > aov(gene ~ tissue + gender +

Dear All, I am a bit struggling with the many packages for Markov models available in R. Apologies for now posting a code snippet, but I am looking for some guidance here. Please consider a set like the one below (which you can get with data<-read.csv('http://dl.dropboxusercontent.com/u/5685598/data_table.csv') ). ID therapy age1 age2 EFS 7308 ormo_lunga 78

Dear R-help members, Apologies for the trouble. I have a question : Essentially, I have a dataset which stores genetic variations for individual patients. Each individual patient can have more than one variation, and each new record corresponds to a new variation (thus, both individual patients and variations are non-unique). So the dataset looks something like this ((letters = patients,

For an Xray file system patients have folders and folders have studies. That is: patients folders studies id id id name patient_id folder_id ... label type ... ... The list of studies with their associated folder and patient might look like this: name folder_label study_type

Hi, I am quite new to R and trying to analyze the following data. I have 28 controls and 25 patients. I measured X values of 4 different locations (A,B,C,D) in the brain image of each subject. And X ranges from 0 to 1. I think "control or patient" is a between subject factor and location is a within subject factor. So, controls: 28 patients: 25 (unbalanced data set) respone measure:

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

Dear R-users, I have a data frame containing 2 colums: column 1 is the patient numbers (totally 36 patients), column 2 is patient's response values (each patient has 100 response values). If I produce a boxplot for each patient on the same graph in order to compare them against each other then the boxplots are very small. How can I instead of creating one graph containing 36 boxplots,

Dear R help gurus, I have the following problem and I would be delighted if you could help me. >From a large (1500) cohort of patients we have been taking some measurements (ECG measurements, but its not important). The measurements are ordinal in 4 grades (Grade I-IV, grade IV being the most severe form). Every patients has been measured several times (usually once per year). The

I am trying to determine how to display a list returned from a Rails find(:include => [:children]). I am using the following (which works in the console): @patients = Account.find(session[:account_id]).patients.find(:all, :include => [:patient_details]) How can I address the patient_details to display them in the view? The console even shows a @patient_details instance variable

Hi I have been asked by a colleague to perform a statistical analysis which uses random effects - but I am struggling to get this to work with nlme in R. Help would be very much appreciated! Essentially, the data consists of: 10 patients. Each patient has been given three different treatments (on three separate days). 15 measurements (continuous variable) have been taken from each patient

i am analyzing some data and have a question i hope someone can answer. i want to use this sort of model: lmer( y ~ x + (1 | ID ), family=binomial, weight=w) so i want to explore the relationship between y and x, with a random effect for each patient. my question is this. is this a sensible model to use when the number of observations for each patient ID is often one? I have 305 observations

My environment: Ruby 1.9.2p290, Rails 3.0.9 and RubyGem 1.8.8 unfortunately I have an issue when come across multiple database. The situation is this: I have two model connect with two different database and also establishing association between each other. database connection specifying in each model, look likes class Visit < ActiveRecord::Base self.establish_connection "lab"

Dear R user: I have a question about doing ANCOVA in S-plus or R. I know that many users use lm to do the regression and check the ANCOVA. But is there a way to get the traditional Table form of the ANCOVA test through S-plus (like what we would get from SPSS or SAS)? The problem I’m interested in is whether or not there is a treatment effect on some medical measurement. I will

Hi, I have what I believe is a repeated-measures dataset that I'm trying to analyze using lme(). This is *not* homework, but an exercise in my trying to self-teach myself repeated-measure ANOVA for other *real* datasets that I have and that are extremely similar to the following design. I'm fairly sure the dataset described below would work with lme() -- but it'd be great if anybody