similar to: if statement problem

Hi I was wondering if there is a permutation test available in R for linear models with continuous dependent covariates. I want to do a test like the one shown here. bmi<-rnorm(100,25) x<-c(rep(0,75),rep(1,25)) y<-rnorm(100)+bmi^(1/2)+rnorm(100,2)*x+bmi*x H0<-lm(y~1+x+bmi) H1<-lm(y~1+x+bmi+x*bmi) anova(H0,H1) summary(lm(y~1+x+bmi)) But I want to use permutation testing to

Im doing a project using Rcommander. I have a dataset with 5 variables, BMI being one of them. I would like to find the variance, standard deviation, range, median, etc of BMI. However, everytime I type a command into the script window, (such as var(BMI$BMI,na.rm=TRUE) )an error message pops up saying Object "BMI" not found. I can graph it, work it, do t-test, etc,. It's listed as

Hello, Say I have 2 columns, bmi and gender, the first being all the values and the second being male or female. How would I subset this into males only and females only? I have searched these fora and read endlessly about select[] and split() functions but to no avail. Also the table is not ordered. bmi gender -> bmi gender + bmi gender 1 24.78 male

I am doing a reanalysis of results that have previously been published. My hope was to demonstrate the value of adoption of more modern regression methods in preference to the traditional approach of univariate stratification. I have encountered a puzzle regarding differences between I thought would be two equivalent analyses. Using a single factor, I compare poisson models with and without

Hola a todos, -Estoy estudiando el efecto de dos genotipos (~tratamientos) en la aparición de síndrome metabólico (MetS) con datos longitudinales recogidos a tiempo 0,7,10,15,20 y 25 años. -He hecho un dataframe con las siguientes variables MetS: Síndrome Metabólico (Si=1,No=0) bmi: Indice de masa corporal (IMC) cuando se produce la conversión a MetS+ . Para los que permancen MetS-, esta variable

Dear R-helpers, First I apologize if my question is quite simple I have a large datasets which more 100 variables. For a research I need to change all name of variables with add one or more letters on each variables. For example, > data(Pima.tr) > Pima.tr[1:5,] npreg glu bp skin bmi ped age type 1 5 86 68 28 30.2 0.364 24 No 2 7 195 70 33 25.1 0.163 55 Yes 3 5

Hello, I'm not sure if I'm in the right place with my question... I'm running R on Windows and wrote a function and saved it as .R file. It looks like this: bmi <- function(weight, height) { bmi <- weight / height^2 bmi } If I want to use this function, I have to mark everything and then press Ctrl-R. But then everything single line is executed on the command line,

hi everyone, wondering if you could help me with a novice problem. I have a data frame called subjects with a height and weight variable and want to calculate a bmi variable from the two. i have tried: attach(subjects) bmi <- (weight)/((height/100)^2) but it comes up with the error: Warning messages: 1: In Ops.factor(height, 100) : / not meaningful for factors 2: In Ops.factor((weight),

I am new to R, and I am trying to cut a continuous variable BMI into different categories and can't figure out how to use it. I would like to cut it into four groups: <20, 20-25, 25-30 and >= 30. I am having difficulty figuring the code for <20 and >=30? Please help. Thank you. -- View this message in context:

Dear R-experts, I am trying to bootstrap (and average) the median squared error evaluation metric for a robust regression. I can't get it. What is going wrong ? Here is the reproducible example. ############################# install.packages( "quantreg" ) library(quantreg) crp <-c(12,14,13,24,25,34,45,56,25,34,47,44,35,24,53,44,55,46,36,67) bmi

Hello, How would you go about handling the following situation? This is on R 2.12.0 on Ubuntu 32-bit. I have a wrapper function to lm. I want to pass in a subset argument. First, I just thought I'd use "...". ## make example reproducible set.seed(123) df1 <- data.frame(age = rnorm(100, 50, 10), bmi = rnorm(100, 30, sd = 2)) ## create a wrapper using

Hi gang, In 500 words or less (if possible), please explain what is a legal music-on-hold file? My boss hates the stuff provided with the distribution and I figure that I'm asking for trouble if I take my Les Mis tracks and run them through Audacity and SOX to make new files. Thanks in advance Danny Nicholas -------------- next part -------------- An HTML attachment was

Hello, I’m not sure if this is the right place to ask beginner questions. If not, please direct me to the appropriate place. I’m writing my first llvm program and I’m trying to call an intrinsic, but failing. So far this is what I have: declare ccc i32 @llvm.x86.bmi.pdep.32(i32, i32) @.str2 = private unnamed_addr constant [4 x i8] c"%d\0A\00", align 1 declare i32 @printf(i8*, ...)

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

Dear all For my research, I am learning classification now. I was trying some example about classification tree pakages, such as tree and rpart, for instance, in Pima.te dataset have 8 variables (include class=type): library(rpart) library(datasets) pima.rpart <- rpart(type ~ npreg+glu+bp+skin+bmi+ped+age,data=Pima.te, method='class') plot(pima.rpart, uniform=TRUE) text(pima.rpart)

  I am trying to used "ordgee" from "geepack" for an ordinal dataset. When I write the code it returns  "Warning message:In binomial(link) : use of binomial(link=link) is deprecated" , but the program runs. Even when I run your example for "ohio" and "respdis", it returns the same error. Please guide me [[alternative HTML version deleted]]

Hello I would like to pass a model formula as an argument to the with.mids function from the mice package. The with.mids functon fits models to multiply imputed data sets. Here's a simple example library(mice) #Create multiple imputations on the nhanes data contained in the mice package. imp <- mice(nahnes) #Fitting a linear model with each imputed data set the regular way works

Hello, How can I run a backward stepwise regression with part of the variables fixed, while the others participate in the backward stepwise analysis? Thank you, Einat -- View this message in context: http://r.789695.n4.nabble.com/Stepwise-analysis-with-fixed-variables-tp4650015.html Sent from the R help mailing list archive at Nabble.com.

Hello, If you want to bootstrap a statistic, I suggest you use base package boot. You would need the data in a data.frame, see how you could do it. library(boot) bootMedianSE <- function(data, indices){ d <- data[indices, ] fit <- rq(crp ~ bmi + glucose, tau = 0.5, data = d) ypred <- predict(fit) y <- d$crp median(y - ypred)^2 } dat <-

Hi, I am trying to change a SAS macro to R. here is my code. I get an error at the last line. attach(fram) dset1<-cbind(AGE,BMI,DEATH) > BMIGRP<-cut(BMI,breaks=3,right=TRUE) > AGEGRP<-floor(AGE/10)-2 > dset<-cbind(AGEGRP,BMIGRP,DEATH) > maxage<-max(dset[,1]) > minage<-min(dset[,1]) > #maxcls<-dset[,2] > #mincls<-dset[,2] >