search for: agecat

...to hit the published numbers on the nose. I am trying to replicate any of the following: the stdize and stdweight parameters from a Stata complex survey analysis command (like this) svyset [w= WEIGHTVAR], psu(PSUVAR) strata(STRATAVAR) vce(linearized) svy: mean VARNAME, stdize(agecat) stdweight(agewt) the stdvar and stdwgt parameters from a SUDAAN proc descript call the ESTIMATE statement in a PROC SURVEYREG (used to generate adjusted means) in SAS version 9.2 I am attempting to match figure 1 from nchs data brief #92 exactly using R. The data are here: http://www....

I am new to R. I have a data set like this (given below is a fictional dataset): AgeCat FINWT 1 98 2 62 1 75 3 39 4 28 2 47 2 66 4 83 1 19 3 50 I need to calculate the weighted distribution of the variable AgeCat. In SAS i can do: proc freq data=ageval; tables agecat; weight finwt; run; What or is there an equivalent in R? TIA, Krishnan -- Krishnan Viswanathan 1101 High Mead...

...ave a set of data that includes various data columns. One if the survival time and another if a continuous variable of ages. I want to put the ages into intervals so that I can then perform the Kalpan Meier test. I am trying to use the following code to build a column with the age group numbers in agecatagory<-c( ) for (i in 1:137) { { if(age[i]<=46) {agecat[i]<-1} if(age[i]>46 & age[i]<= 58) {agecat[i]<-2} if(age[i]>58) {agecat[i]<-3} } agecatagory<-c(agecatagory, agecat[i]) } I have been getting various errors for various things and have finally got it so that on...

Dear, I want to fit an inverse gaussion distribution to a data set. The predictor variables are gender, area and agecategory. For each of these variables I've defined a baseline e.g. #agecat: baseline is 3 data<-transform(data, agecat=C(factor(agecat,ordered=TRUE), contr.treatment(n=6,base=3))) The variable 'area' goes from A to F (6 areas: A,B,C,D,E,F) How can i manipulate the data to set the b...

Hi! I am quiet new with R and I have some problems to perform a posthoc test with an lme model. My model is the following: >lme1<-lme(eexp~meal+time, random=~1|id,na.action=na.omit) and then i try to get a post hoc test: >summary(glht(lme1,linfct=mcp(meal="Tukey))) but I get a warning message: Erreur dans as.vector(x, mode) : argument 'mode' incorrect Thank you for your

...run GLM. The error only occurs when I have all independent variables in the model. When I drop one independent variable, the model runs fine. Can anyone help me understand what the error means and how I can correct it? Thank you, John > fit11<-glm(AAMTCARE~BMI+BMIsq+SEX+jPHI+jMEDICAID+factor(AgeCat)+ + factor(jINDINC)+jMARSTAT+jEDUCATION+factor(jsmokercat)+factor(jrace),data=SimData,family=Gamma(link="log")) Warning: step size truncated due to divergence Error in glm.fit(x = X, y = Y, weights = weights, start = start, etastart = etastart, : inner loop 1; cannot correct step size...

I have a variable which is roughly age categories in decades. In the original data, it came in coded: > str(xxx) 'data.frame': 58271 obs. of 29 variables: $ issuecat : Factor w/ 5 levels "0 - 39","40 - 49",..: 1 1 1 1... snip I then defined issuecat as ordered: > xxx$issuecat<-as.ordered(xxx$issuecat) When I include issuecat in a glm model, the result

R Fans-- I am having problems with the following code. It worked under R 2.6.0 but not in 2.7.0. > library(Epi) > df <- read.table( "c:/Documents and Settings/Troy S/My Documents/debug_chisq_080613b.txt") > summary(df) cvd agecat Min. :0.0000 (0,40] :1 1st Qu.:0.0000 (40,60]:2 Median :0.0000 Mean :0.3333 3rd Qu.:0.5000 Max. :1.0000 > fa <- as.factor(df$cvd) > fb <- as.factor(df$agecat) > stat.table(index=list("a"=fa, "...

I am doing group wise plots by using the following commands; it shows errors that I do not know how to fix it. Please help. xyplot(within.2.special.care ~ agecat| mco.cms.ind, neuro, panel = function(x,y){ + panel.grid() + panel.xyplot(x,y) + panel.loess(x,y, span =1)}) Error: couldn't find function "xyplot" [[alternative HTML version deleted]]

Hi, I'm working on some social networks and I managed to create the graphs with labels and edges weight, but I would also like to change the size of the vertices according to the age of the persons in the network and the shape according to the gender. Now for the age, I have people with ages between 20 and 78, and I would like to have 4 categories (sizes): 20-35, 36-50, 50-65, >65. I have

Dear Colleagues, We are attempting to create trees using R with our Ruby on Rails application. However, we are running into a problem involving the creation of the graphic. We would like them to be in either jpg or png format so that users can save, but due to a lack of control over our sever we are unable to start X11 server. Is there a way to create these images without using X11 server?

...t(myimp$imputations[[i]]$t0rcd4pc,breaks=c(-1,25,1000000000))) colnames(myimp$imputations[[i]])[16]<-c("cd4pccat") myimp$imputations[[i]] <- cbind(myimp$imputations[[i]],cut(myimp$imputations[[i]]$ageatran,breaks=c(-1,36,1000000000))) colnames(myimp$imputations[[i]])[17]<-c("agecat") myimp$imputations[[i]] <- cbind(myimp$imputations[[i]],cut(myimp$imputations[[i]]$t0rwfa,breaks=c(-1000,-3,-2,10))) colnames(myimp$imputations[[i]])[18]<-c("wfacat") myimp$imputations[[i]] <-cbind(myimp$imputations[[i]],cut(myimp$imputations[[i]]$t0rwfh,breaks=c(-1000,-3,-...

Hello R-experts, I have a set of data as follows: age time 1 28 1 2 53 2 3 53 3 4 36 4 5 54 4 6 46 4 7 45 5 8 31 6 9 53 7 10 35 7 11 62 8 12 19 8 13 43 2 14 51 3 15 45 0 16 48 2 17 49 3 18 57 2 19 45 3 20 27 10 21 33 12 22 29 14 23 46 16 24 45 19 25 43 2 26 28 6 27 50 7 28 28 4

I am new in using R. I want to know all about building decision tree model in R. Few options which I searched are rpart and rattle to build a decision tree.Both the functions are giving me splits which are statistically appropriate. But I am not able to figure out how to change those splits as per my business requirement. for example : the automatic split of Age by using rattle is > 30 and

Dear r-help, I am trying to plot several scatter plots with marginal histograms on one page. Ideally, a page is equally divided into 4 figure regions. Within each figure region, a scatter plot with marginal histograms will be plotted. I followed Dr. Paul Murrell's code released online to successfully plot the scatter plot with marginal histograms. The code applies "layout()" to

...R] xyplot To: R-help at stat.math.ethz.ch Message-ID: <000001c33c04$04b2d370$db8c5c90 at Outcome.wisc.edu> Content-Type: text/plain I am doing group wise plots by using the following commands; it shows errors that I do not know how to fix it. Please help. xyplot(within.2.special.care ~ agecat| mco.cms.ind, neuro, panel = function(x,y){ + panel.grid() + panel.xyplot(x,y) + panel.loess(x,y, span =1)}) Error: couldn't find function "xyplot" [[alternative HTML version deleted]] ------------------------------ Message: 35 Date: Thu, 26 Jun 2003 19:03:36 +02120 (MEST) From...