similar to: Multiple t.test

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

Hi, I have been using R to do multiple analyses of variance with two covariates, but recently found that the results in SPSS were very different. I have check several books and web resources and I think that both methods are correct, but I am less familiar with R, so I was hoping someone could offer some suggestions. Oddly simple ANOVA is the same in SPSS and R. Including covariates improves the

Hi, This code is trying to produce a series of graphics files, with plots of male and female disease rates by age, one plot per disease. The dataframe contains a variable 'Age' and a set of 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

Hello R gurus, I have a data set from which i have to extract the gender and age matched rows from controls and disease group disease<-paste(rep(c('y','n'),11)) gender<-paste(rep(c('m','f'),11)) mcp<-rnorm(700,1400) age<-rnorm(32,34) dat<-data.frame(disease=disease,sex=gender,Dr_age=age[1:22],MCP=mcp[1:22]) I have other categorical variables also to

I fit the following model using glmmPQL from MASS: fit.glmmPQL <- glmmPQL(ifelse(class=="Disease",1,0)~age+x1+x2,random=~1|subject,family=binomial) summary(fit.glmmPQL) The response is paired (pairing denoted by subject), although some subjects only have one response. Also, there is a perfect positive correlation between the paired responses. x1 and x2 can and do differ within each

Hi, I'm sure this is simple, but I haven't been able to find this in TFM, say I have some data in R like this (pasted here: http://pastebin.com/raw.php?i=sjS9Zkup): > head(df) gender age smokes disease Y 1 female 65 ever control 0.18 2 female 77 never control 0.12 3 male 40 state1 0.11 4 female 67 ever control 0.20 5 male 63 ever state1 0.16

hi, people How can we compare two probit models brought out from the same data? Let me use the example used in "An Introduction to R". "Consider a small, artificial example, from Silvey (1970). On the Aegean island of Kalythos the male inhabitants suffer from a congenital eye disease, the effects of which become more marked with increasing age. Samples of islander males

I have to study censured datas concernig the occurence of infection at the point of insertion of catheter in patients with renal disease. Catheter may be removed for ather reasons than infection, in this case, the observation is censored. Each has exactly 2 observations. The question are the pronostic factors of infection (the other variables are; age, sex, type of renal disease...). Could you

## 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

Dear list, I have the following data set id 1 2 3 4 5 6 7 8 9 10 disease a b c d e f g h i j age 23 40 32 34 25 32 22 35 29 21 city NY LD NY SG NY LD VG SA LD SG sex 1 1 2 2 2 2 1 1 1 2 treat_a y y y y treat_b n n n n n n ques1_1 2 4 5 6 8 3 1 2 4 5 ques1_2 6 4 5 12 10 9 8 4 5 7

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.

Dear list, Hello! I have a question about how to print a label in the plot. I am using the following code: <pdf("mel4_chr3_11cancer_cghFLasso.pdf", height=6, width=5);plot(Disease.FL, index=i, type="Single",main="Plot of Labels");dev.off(); But "Plot of Labels" has not been printed. Any suggestions? Thanks a lot! Allen

Dear list, I have a question about using plot(). I tried the code: <pdf("mel_chr_all_13cancer_cghFLasso_all.pdf", height=6, width=11);plot( Disease.FL, index=1:4, type="All");dev.off(); and it went through well which outputed 4 plots for 4 samples in one page. But if I increase the numbers of plots(samples) which I want, saying to 11,

Hi, I'm totally new to R so I apologise for the basic request. I am looking at the incidence of a disease over two time periods 1990-1995 and 2003-2008. I have counts for each year, subdivided into three disease categories and by males/females. I understand that I need to analyse the data using poisson regression and have managed to use the pois.daly function to get age-sex adjusted rates and

Hello, I have a problem regarding calculation of Cumulative Incidence Function. The event of interest is failure of bone-marrow transplantation, which may occur due to relapse or death in remission. The data set that I have consists of- lifetime variable, two indicator variables-one for relapse and one for death in remission, and the other variables are donor type (having 3 categories), disease

Hi All, I'm fitting an proportional odds model using vglm() from VGAM. My response variable is the severity of diseases, going from 0 to 5 (the severity is actually an ordered factor). The independent variables are: 1 genetic marker, time of medical observation, age, sex. What I *need* is a p-value for the genetic marker. Because I have ~1.5 million markers I'd rather not faffing

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

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

Dear All, Does anybody have experience with R package pbatR (http://cran.r-project.org/web/packages/pbatR/index.html)? I am trying to use it to analyze the family-based case-control data, but the package totally doesn?t work on my computer. I contacted the authors of the package, but I haven?t heard anything from them. Following the package manual, I tried the simple example as below:

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