similar to: Subsetting problem data

Hello, I have a data set where there are multiple "cycles" per "patient," and I want to exclude from my data set instances where a variable was not measured every cycle. The difficulty is that the patients have different cycles; some have cycles 1,2, and 3, others only have 1 and 3 (and everything in between). Therefore, I'm having difficulty in in distinguishing between

I have a longitudinal competing risk data of the form: ID COMPL SEX HEREDITY 1 0 1 2 1 0 1 2 1 3 1 2 2 0 0 1 2 1 0 1 2 2 0 1 2 2 0 1 3 0 0 1 3 0 0 1 3 0 0 1 3 0 0 1 3 2 0 1 4 0 1 2 4 0 1

I have a text file that has semi-colon separated values. The table is nearly 10,000 by 585. The files looks as follows: ******************************************* First line: Skip this line Second line: skip this line Third line: skip this line variable1 Variable2 Variable3 Variable4 Unit1 Unit2 Unit3 10 0.1 0.01 0.001 20

I'm attempting to change a data set by compressing rows into columns. Currently there are several rows that all have information about one "patient," but at different cycles. I'm trying to make each patient only have one row in the data set. Does anyone know a good way to combine data sets by factor level? I've separated the groups into different subsets by cycle, but not

Dear R users, A co-worker and I are writing a function to facilitate graph plotting in R. The function makes use of a lot of lists in its defaults. However, we discovered that R does not necessarily preserve the defaults if we were to input them in the form of list() when initializing the function. For example, if you feed the function codes below into R: myfunction=function( list1=list

Hello, I'm using SPSS at work but really would like to switch to R. Right now I'm trying to learn R in reproducing calculations I did with SPSS but am stuck with something that is quite simple and comprehensible in SPSS-Syntax: IF (variable1.fac = 0 AND variable2.num = 0) variable3=1. IF (variable1.fac = 0 AND variable2.num >= 1) variable3=2. IF (variable1.fac = 1 AND variable2.num =

I am attempting to replicate some of my experience from SAS in R and assume there are best methods for using a combination of summary(), subset, and which() to produce a subset of mean values by categorical or ordinal factors. within sas I would write proc means mean data=dataset; class factor1 factor2 var variable1 variable2; RUN; producing an output with means for each variable by factor

Dear list, I am trying to use lme to build the analogue of the following SAS MIXED random specification: random int+Variable1+Variable2 /subject = Subject group=Condition type=vc; which gives a Condition-blocked heterogeneity in the random effects variance-covariance matrix. Needless to say, I have a hard time in specifying Condition-specific heterogeneities in the variance-covariance

Listers, I have a question regarding correlation matrices. It is fairly straight forward to build a correlation matrix of an entire data frame. I simply use the command cor(MyDataFrame). However, what I would like to do is construct a smaller correlation matrix using just three of the variable out of my data set. When I run this: cor(MyDataFrame$variable1,

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Hi there, I have a huge dataframe containing 70,000 observations. I have filtered this dataframe (let it's name be "transformed_dataframe") as I wanted to select only those observations which are greater than or equal to 60,001 regarding the very first identity column. So I have a transformed dataframe now including 10,000 obeservations (from 60,001 - to 70,000) and if you send

Hello, How do you print a variable name in a for loop? I'm trying to construct a csv file that looks like this: Hello, variable1, value_of_variable1, World, Hello, variable2, value_of_variable2, World, Hello, variable3, value_of_variable3, World, Using this: for (variable in list(variable1, variable2, variable3)){ cat("Hello,", ???variable???, variable, ",

Hi guys I seem to be having a problem, I don't know if it's a bug or whether I'm just doing it incorrectly. I want to set about 3 channel variables when I originate a call via AMI. All the documentation I have found says to do it like this: Variable: variable1=value|variable2=value|variable3=value However when I do this it runs them all together and I end up with:

Hello R-Helpers, I am not sure if it is a very simple question but I would like to use two (...) in a function, for example, this is a script where I would like to input the variable names (in one of the (...)) and the variances associated to those variables which are not calculated in the script because there is a specific software to calculate it (the other (...)) data <- function

Hi everyone, I’m looking for a clever bit of code to replace NA’s with a specific score depending on an indicator variable. I can see how to do it using lots of if statements but I’m sure there most be a neater, better way of doing it. Any ideas at all will be much appreciated, I’m dreading coding up all those if statements!!!!! My problem is as follows: I have a data set with

Dear list, I have a set of 100+ variables. I would like to have one by one crosstables for each variable. I started with table(variable1, variable2) table(variable1, variable3) table(variable1, variable4) ... table(variable2, variable3) table(variable2, variable4) ... It seems rather tedious. Any better ideas around? Thanks for any help! Gerit -- NUR NOCH BIS 31.01.! GMX FreeDSL -

Hello, I didn't give enough information when I sent an query before, so I'm trying again with a more detailed explanation: In this data set, each patient has a different number of measured variables (they represent tumors, so some people had 2 tumors, some had 5, etc). The problem I have is that often in later cycles for a patient, tumors that were originally measured are now missing (or

Hola a todos Estoy cargando una base de datos a R llamada "Base", desde excel. A la hora de utilizar funciones como: >pairs(Base) Error in pairs.default(Base) : non-numeric argument to 'pairs' Una forma de arreglar este problema es utilizando la funcion as.numeric(), pero me toca hacerlo variable por variable: >Base$Variable1<-as.numeric( Base$Variable1)

Hello, I have many hundred variables in my longitudinal dataset and lots of missings. In order to plot data I need to remove missings. If I do > data <- na.omit(data) that will reduce my dataset to 2% of its original size ;) So I only need to listwise delete missings on 3 variables (the ones I am plotting). data$variable1 <-na.omit(data$variable1) does not work. Thank you

Hello I wrote a bootstrap program in C language that is called and run by R. When I tried it, it is slow and I'm trying to write and run the whole thing in C. But I cannot use handy functions in R and need to figure out how to write those functions by myself. Is there any way that I can get the actual codes that implement functions in R so that I can translate them into other languages? For