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## Question1: How to define IV with interaction alone, without main effects? ## Question2: Should Type III ANOVA in package car be independent of the factor level order? ## data from http://www.otago.ac.nz/sas/stat/chap30/sect52.htm drug <- c(t(t(rep(1,3)))%*%t(1:4)); disease <- c(t(t(1:3)) %*% t(rep(1,4))); y <- t(matrix(c( 42 ,44 ,36 ,13 ,19 ,22 ,33 ,NA ,26 ,NA ,33 ,21 ,31 ,-3 ,NA

I would be grateful for advice about the following problem. It's not directly R-related, but I'm hoping that R will help me analyse the following data. I have a table which indicates the progression of a certain age-related disease. At a certain point in time, a population was sampled; and I have measurements for the age of each individual, and their disease stage. (Disease stage is an

Dear R experts, Suppose I have an data frame likes this: > example <- data.frame(age=c(1,2,3, 4,5,6), height=c(100,110,120,130,140,150), disease=c(TRUE, TRUE, TRUE, FALSE, FALSE, FALSE)) > example age height disease 1 1 100 TRUE 2 2 110 TRUE 3 3 120 TRUE 4 4 130 FALSE 5 5 140 FALSE 6 6 150 FALSE Is there anyway to compare the age and

I have been trying to open data that I have saved in an excel spread sheet. I saved it as a csv. Then I tried using the read.csv command. However, everytime I do this-- diseasedat<-read.csv("M:/sloan/R/disease/disease.csv", sep=, header = TRUE, fill= TRUE)-- I get an error message: Error in file(file, "r") : unable to open connection In addition: Warning message:

...variables called 'Male_CVD, Female_CVD,Male_RTA,Female_RTA, and so on. For each disease, I want to pull out the column of data containing the word 'Male' and plot this against age, and then add a line to the plot for the corresponding column containing 'Female'. -- attach(data) Diseases <- c("Cardiovascular disease","Road Traffic Injury", ... ,"All causes") Male <- names(data)[grep("Male",names(data))] Female <- names(data)[grep("Female",names(data))] #Disease contains disease labels in the correct order, and Male and Fem...

I'm having trouble figuring out how to format Date variables when used as axis labels in graphs. The particular case here is an attempt to re-create Nightingale's coxcomb graph with ggplot2, where I'd like the months to be labeled as "Mar 1885", "Apr 1885", using a date format of "%b %Y" applied to label the dates, or really anything other than

Hi R help list I'm simulating logistic regression data with a specified odds ratio (beta) and have a problem/unexpected behaviour that occurs. The datasets includes a lognormal exposure and diseased and healthy subjects. Here is my loop: ors <- vector() for(i in 1:200){ # First, I create a vector with a lognormally distributed exposure: n <- 10000 # number of study subjects

Dear UseRs, Suppose I have data regarding smoking habits of a prospective cohort and wish to determine the risk ratio of colorectal cancer in the smokers compared to the non-smokers. What do I do at the end of the study with people who die of heart disease? Can I just censor them exactly the same as people who become uncontactable or who die in a plane crash? If not, why not? I'm thinking

Hi I got an error message using datadist() from Design package: > library(Design,T) > dd <- datadist(beta.final) > options(datadist="dd") > lrm(Disease ~ gsct+apcct+rarct, x=TRUE, y=TRUE) Error in eval(expr, envir, enclos) : object "Disease" not found All variables inclduing response variable "Disease" are in the data frame

Greeting. Dear Mr/Mrs/Miss, OTU ID Health Disease Bacterial 1 0.29 0.34 Bacterial 2 0.25 0.07 Bacterial 3 0.06 0.06 Bacterial 4 0.07 0.09 Bacterial 5 0.02 0.05 Above show the first 6 data sets, may I ask that the reason of R show the error like "Error in cor(data) : 'x' must be numeric" ? And how to solve it? Besides, isn't this data can conduct correlation matrix?

Hi Chin Yi, If you are trying to correlate "Health" with "Disease", i.e. cydf<-read.table(text="OTU ID Health Disease Bacterial 1 0.29 0.34 Bacterial 2 0.25 0.07 Bacterial 3 0.06 0.06 Bacterial 4 0.07 0.09 Bacterial 5 0.02 0.05", header=TRUE) print(cor(cydf$Health,cydf$Disease)) [1] 0.7103517 If you are getting that error, it probably means that

hello, I asked about this simulation a few days ago, but still i can't get what i need. I have 2 units: icu and regular. from icu I want to take 200 observations from binomial distribution, when probability for disease is: p=0.6. from regular I want to take 300 observation with the same probability: p=0.6 . the distribution to detect disease when disease occurred- *for someone from icu* - is:

Dear R-Help List, I'm trying to simulate data from a conditional distribution, and haven't been able to modify my existing code to do so. I searched the archives, but didn't find any previous post that matched my question. n=10000 pop = data.frame(W1 = rbinom(n, 1, .2), W2 = runif(n, min = 3, max = 8), W3 = rnorm(n, mean=0, sd=2)) pop = transform(pop, A = rbinom(n, 1,

On 2017-07-05 11:56, Jim Lemon wrote: > Hi Chin Yi, > If you are trying to correlate "Health" with "Disease", i.e. > > cydf<-read.table(text="OTU ID Health Disease > Bacterial 1 0.29 0.34 > Bacterial 2 0.25 0.07 > Bacterial 3 0.06 0.06 > Bacterial 4 0.07 0.09 > Bacterial 5 0.02 0.05", > header=TRUE) >

Please explain me as what it means and how this analysis can be done using R and which library(ies) are needed. Thanks -- View this message in context: http://www.nabble.com/Regression-using-age-and-Duration-of-disease-as-a-continous-factors-tp24574133p24574133.html Sent from the R help mailing list archive at Nabble.com.

I was at a lecture the other day and I saw a presentation of very neat (short) animation modeling epidemic disease spread over a map region. When I ask what software they used they mentioned SAS. Do you know if there are equivalent resources in R to model the spread of disease with animation output? My search in R-help and google didn't lead to any document (though I found a couple of

...report has several sections along the lines of: \section*{Disease X} <<MapX,fig=TRUE,echo=FALSE>>= image(vectorx,vectory,matrixz) @ Notes with or without Sexpr{a}. \vfill \pagebreak \section*{Disease Y} <<MapY,fig=TRUE,echo=FALSE>>= ...etc. Often one or more of the diseases is not observed (all values in matrixz are 0), in which case I would prefer not to display the section at all. Does any one no whether it is possible automate this with Sweave? Mikkel

...sub-lists/dataframes, which I want to specify with a name vector and paste together the object name and pass it on to a function. Here an (hopefully) instructive example #Data Example gnuff<-list() gnuff$IHD$LE<-66 gnuff$LUNG$LE <-55 #This is the list, where I collect data for different diseases at the second level of the list #Now I want to do calcualtions just for these two diseases and the sub-list "LE" within these diseases nam <- c("LUNG","IHD") for(i in 1:2) x[i] <- paste("gnuff",nam[i],"LE",sep="$") /2 x #So I try...

I am relatively new to R and am looking for advice, ideas or both... I have a data set that consists of pathogen population sizes on individual plant units in an experimental field plot. However, in order to estimate the pathogen population sizes I had to destroy the plant unit and could not determine if that plant unit became diseased or to what extent it would have become diseased. I

Hello all! I am once again analyzing patient survival data with chronic liver disease. The severity of the liver disease is given by a number which is continuously variable. I have referred to this number as "meld"--model for end stage liver disease--which is the result of a mathematical calculation on underlying laboratory values. So, for example, I can generate a Kaplan-Meier plot