similar to: matching by gender and age

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, i am a biologist who needs to do some ttest between disease and non disease, sex, genotype and the serum levels of proteins on a large number of individuals. i have been using excel for a long time but it is very tedious and time consuming. i am posting the data below and ask your help in generating a code to get this analysis done in R. thanks gender disease genotype data M N CC

I currently have a data set in which gender is inputed as "Male" and "Female" , and I'm trying to convert this into "1" and "0". I found a website which reccomended using two commands: data$scode[data$sex=="M"] <- "1" data$scode[data$sex=="F"] <- "2" to convert to numbers, and: data$scode <-

Hello Gurus I have two correlation matrices 'xa' and 'xb' set.seed(100) d=cbind(x=rnorm(20)+1, x1=rnorm(20)+1, x2=rnorm(20)+1) d1=cbind(x=rnorm(20)+2, x1=rnorm(20)+2, x2=rnorm(20)+2) xa=cor(d,use='complete') xb=cor(d1,use='complete') I want to combine these two to get a third matrix which should have half values from 'xa' and half

Thanks for the feedback. I did some research and it looks like you were calling over international lines. It also appears that there was high than average static on the line, which is not normal for my system. It's true that I threw my recordings together quickly and the beep was supposed to be funny - it was actually me saying "beeeeeep". However, the static and noise you received

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

Hello, All, I have a dataset that looks like this: x <- matrix(c( 0, 0, 0, 0, 0, 0, 0, 1, 0, 0, 1, 0, 0, 1, 0, 1, 2, 1, 1, 2, 1, 1, 3, 1, 1, 3, 1, 1, 3, 1), ncol = 5, byrow = T, dimnames = list(1:10, c("gender", "race", "disease"))) I want to write a function to produce several matrices including only ?TRUE? and ?FALSE? for the different levels of the

I need your help: please help test the gender detection module at 575-613-4392. I wrote a gender detection module and thought I'd try it out. It only takes a second. I've been showing 90%+ accuracy and I want to make sure it's working correctly. Rain and significant background noise seems to throw it off, so I still have a bit of work to do. Have your friends and significant others

Hello, I have data in a dataframe with 139104 rows which is multiple of 96x1449. i have a phenotype file which contains the phenotype information for the 96 samples. the snp name is repeated 1449X96 samples. I haveto merge the two dataframes based on sid and sen. this is how my two dataframes look like dat<-data.frame(snpname=rep(letters[1:12],12),sid=rep(1:12,each=12),

Hi all: My data has 3 variables: age(3levels : <30y=1 30-50y=2, >50y=3) gender(Male=0, Female=1) CD4 cell count(raw lab measurement) y(1:death 0:alive) I perform logistic regression to find out the factors that influence y. result<-glm(y ~ factor(age) + factor(gender) + CD4,family = binomial) >From the result,I can get OR(Odds Ratio) of gender via exp(Estimate of Female,

I apologize in advance if this is posted all ready I have not been able to find any information about it. I have this data frame and I want to sort smoking by retlevel. Age Gender BMI Calories Fat Fiber Alc retlevel Smoking 1 64 Female 18.87834 1828.0 63.4 14.7 0.0 Normal Non-Smoker 2 25 Female 20.64102 1517.4 59.1 5.9 0.0 Normal Smoker 3

## 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

Hi all, I want to know how to perform the test Breslow-Day test for homogeneity of odds ratios (OR) stratified for svytable. This test is obtained with the following code: epi.2by2 (dat = daty, method = "case.control" conf.level = 0.95, units = 100, homogeneity = "breslow.day", verbose = TRUE) where "daty" is the object type table svytable consider it, but

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:

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 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 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

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 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