search for: age1

Hello, I want to create a new variable which includes 4 age categories in this way: if (age>=12 && age<32) age1==1 if (age>=32 && age<52) age1==2 if (age>=52 && age<72) age1==3 if (age>=72 && age<100) age1==4 but I get the results only for the first observation. how can I apply this condition to all observations? Thanks in advance, Sigalit. [[alternative HTM...

Hi I have two processes which take with a certain probability (p1 and p2) x number of years to complete (age1 and age2). As soon as thge first process is completed, the second one begins. I want to calculate the time it takes for the both processes to be completed. I have the following script which gives me the answer, butI think there must be a more elegant way of doing the calculations between the ##...

Dear R-Users, How can I put a pre-defined regression model into to an object of class lm in order to use the predict.lm function. A simplified example: I would normally run a regression analysis on a dataset, > germany<-lm(RENT~AGE1, in.mi01) > summary(germany) Call: lm(formula = RENT ~ AGE1, data = in.mi01) Residuals: Min 1Q Median 3Q Max -12.193 -3.646 -1.009 2.101 49.025 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 13.283639 0.063020 210...

Dear list I'm using the reshape command and want to reshape a wide data set to a long one e.g. I have the variables y1,y2,y3,age1,age2,age3,sex,ethnic I want my new long data set to consist of the variables y (which has been created from y1,y2,y3), age (which has been created from age1,age2,age3), sex and ethnic I have tried to use the command: data1<-reshape(data,varying=list(c("y1","y2","y3&qu...

Hi there, I have a rather large data set and perform the following cox model: test1 <- list(tstart,tstop,death1,chemo1,radio1,horm1) out1<-coxph( Surv(tstart,tstop, death1) ~ chemo1+chemo1:log(tstop+1)+horm1+horm1:log(tstop+1)+age1+grade1+grade1:log(tstop+1)+positive1+positive1:log(tstop+1)+size1+size1:log(tstop+1), test1) out1 Up to here everything works fine (with each covariate having a length of 289205) Now I want to see a specific profile of the above model so I ask for: x11() profilbig2=(survfit(out1,newdata=data.fra...

...4],Age=3:4) l=list(x1,x2) l [[1]] Name Age 1 A 1 2 B 2 [[2]] Name Age 1 C 3 2 D 4 I would like to unlist l to create a dataframe with 2 columns and 4 rows but keeping the format of Name (character) and Age (numeric). Now when I unlist l, I obtain : unlist(l) Name1 Name2 Age1 Age2 Name1 Name2 Age1 Age2 1 2 1 2 1 2 3 4 Is there a way to at least obtain something like A 1 B 2 C 3 D 4 as result from the unlist?? Thanks a lot for your replies Naira -- View this message in context: http://www.nabble.com/unlist---dataframes-tp20358993p2...

Hi, Is there a simple command for computing the standard error of a combination of parameter estimates in a GLM? For example: riskdata$age1 <- riskdata$age riskdata$age2 <- ifelse(riskdata$age<67,0,riskdata$age-67) model <- glm(death~age1+age2+ldl, data=riskdata,family=binomial(link=logit)) And we want to find the standard error of the partial linear predictor for the combination of the two age parameters, age1+age...

...en using na.omit(). To illustrate this problem I will give the example I am working on and the approah I have been using:- data.frame1<-filepath.... attach(data.frame1) #create a new variable using a function new.variable<-rep(1,length(weight3)) for (x in 1:length(new.variable)) {f<-((((age1[x]-7)*(weight[x]-mw))+((age2[x]-7)*(weight2[x]-mw))+((age3[x]-7)* (weight3[x]-mw)))/(((age1[x]-7)^2)+((age2[x]-7)^2)+((age3[x]-7)^2))); new.variable[x]<-f} #then bind it into the existing old data frame data.frame2<-cbind(data.frame1,newvariable) rm(dat.frame1) attach(data.frame2) #everythin...

Hi all, I am hoping someone can help me out with this: If I have dataframe of years and ages and the first column and first row are filled with leading values: Df<- age1 age2 age3 Yr1 1 0.4 0.16 Yr2 1.5 0 0 Yr3 0.9 0 0 Yr4 1 0 0 Yr5 1.2 0 0 Yr6 1.4 0 0 Yr7 0.8 0 0 Yr8 0.6 0 0 Yr9 1.1 0 0 Now the rest of the cells need to be filled according to the previous year and age cell so arbitrarily, cell [2,2] should be value in cell [1,1] * exp(0.3), and c...

Hello R-Users, I have the following problem with the subset function: See the following simple linear model. Here everything works fine: >germany<-lm(RENT~AGE1, in.mi01) However, if a use the same regression equation and only specify a subset, I get an error message: > berlin<-lm(RENT~AGE1, in.mi01, subset=C_X01=="Berlin") Error in lm.fit(x, y, offset = offset, singular.ok = singular.ok, ...) : 0 (non-NA) cases T...

...running regressions with many covariates, most of which remain the same each time (control variables). Instead of writing 30 demographic variables every regression, is there a way I could call them all at once using a variable called, perhaps "demog"? I have tried: > demog <- list(age1, age2, age3) but I get an error when I try to call a list in a regression. I also tried: > demog <- cbind(age1, age2, age3) which allows me to run a regression, but this is not practical because when I subset the original data set and run a regression, this new matrix demog doesn't get s...

...I have a (rather theoretical) programming problem for which I have found a solution, but I feel it is a rather poor one. I wonder if there's some other (more clever) solution, using (maybe?) vectorization or subscripting. A toy example would be: rel1 rel2 rel3 age0 age1 age2 age3 sex0 sex1 sex2 sex3 1 3 NA 25 23 2 NA 1 2 1 NA 4 1 3 35 67 34 10 2 2 1 2 1 4 4 39...

...40,30,11,23,24,56,65,60) id<-c(1,1,3,4,4,6,8,9,9) table1<-cbind(treatment,id,age,y) *the actual data are way more than this*,the id is from 1~500,and not in regular ,some number missing~ all I want to do is put the cases to variable according the id for example when id =1 we have treatment1 age1 y low 50 20 high 60 40 this will generate a new matrix for this example I will have 6 new matrix,according to id. it is reasonable to do this in loop for,but the I met some problem: 1:how to automatically generate the new title such as treatment1 and age1 until tr...

Greeting R helpers J I am not familiar with R but I have to use it to analyze data set that I have (30,000 20,000) I want to change the structure of the dataset and I am wondering how that might be possible in R A main data looks like this: some entities are empty Age No. Age No. Age No. Center1 5 2 8 7

...Preacher's Bootstrapping test for mediation (Preacher & Hayes, 2004). I have attempted to use the mediate package to set this up, using code that looks basically like this: model.m <- lm(data$outcome ~ data$mediator + desirdata$predictor) model.y <- lm(data$outcome ~ data$predictor) age1 <- mediate(model.m, model.y, treat = "predictor", mediator = "mediator", conf.level=.95, boot=TRUE, sims=50) However, I get an error indicating that the number of observations doesn't match across the two models. This may be true, because it's a somewhat large samp...

...between value and Cohort could be glm(value ~ Age/Cohort -? 1, family =......, data = .....) glm(value ~ Age/(Cohort + I(Cohort^2)) - 1, family =......, data = .....). The latter commands would provide estimates of the age-specific intercept, linear, and quadratic coefficients, as in value_Age1 <- intercept_Age1 + linear_Age1*Cohort + quad_Age1*Cohort^2 value_Age2 <- intercept_Age2 + linear_Age2*Cohort + quad_Age2*Cohort^2 This is standard. One would choose among the above models via analysis of variance or AIC. Now assume that I have external knowledge that tells me that ther...

...rt manual. It is a bit peculiar because my data base is already an R object called "japan". I guess it is not yet a data set, and I don't know how to manipulate variables from it. When I type "japan", here is an extract of what I get. LDP NFP SKG JCP gender education age1 80 75 80 0 male 1 752 75 80 50 20 female 1 643 100 25 100 0 male 2 564 75 50 25 50 male 2 525 75 50 50 0 male 4 52 I have saved the following objet in a file called "japan.RData". Then I have tried the fol...

...f Binomial? How will it affect my results? (b) How do I interpret the "R" result as given below? I know all the variables are significant. How do I get Log Likelihood ratio, Odds ratio etc.? Please can anyone help me out. With warm regards Madhavi R OUTPUT Call: glm(formula = Y ~ Age1 + Age2 + Sex + Education + Profession + SavingsAccount +     CurrentAccount, family = binomial(link = logit), data = ons) Deviance Residuals:      Min        1Q    Median        3Q       Max   -3.21142  -0.42556  -0.15911  -0.02954   3.02465   Coefficients:                   Estimate Std. Error...

...899 10.025943 [8] 9.971243 10.177766 9.265793 9.415818 10.099874 10.238829 9.575591[15] 9.560879 9.617891 9.617891 10.158160 10.592377 10.068443 >summary(glm(tmp1 ~ -1 + age, data=data.frame(as.vector(as.matrix(tmp1)), age)))$coefficients Estimate Std. Error t value Pr(>|t|)age1 9.541423 0.1611603 59.20456 3.380085e-19age2 10.083694 0.1611603 62.56935 1.479781e-19age3 9.739813 0.1611603 60.43557 2.485380e-19age4 9.748297 0.1611603 60.48821 2.453251e-19age5 10.109218 0.1611603 62.72773 1.424913e-19 m1 <- data.frame(tmp1, gp) >sapply(age, function(x) sd(m1[m1...

...version of it, to the 'stats' package, with the other multinomial functions reside. I'm using R to export data to text files, which are input data for an external model written in C++. Parts of the data are age distributions, in the form of relative frequency in each year: Year Age1 Age2 ... Age10 1980 0.123 0.234 ... 0.001 ... ... ... ... ... Each row should sum to exactly 1. The problem is that when I preprocess each line in R as p<-a/sum(a), occasionally a line will sum to 0.999, 1.002, or the like. This could either crash the external model or...