similar to: output data in a fixed format

Hi All, I am new to post question on this list. I apologize if this question is too easy or irrelevant. I am doing a simulation study and I need to read a data file that can be easily read by SAS. So, what I try to do is to execute SAS in R and then read the output of SAS to R. I try the following code but it didn't work. system("c:\\program files\\sas institute\\v8\\sas.exe

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

In clinical trial data preparation and many other data situations, the statistical programmer needs to merge and re-merge multiple input files countless times. A syntax for merging files that is clear and concise is very important for the statistical programmer's productivity. Here is how Vilno does it: inlist dataset1 dataset2 dataset3 ; joinby variable1 variable2 where ( var3<=var4 ) ;

Dear R users, I was wondering if anyone knows how to obtain(subset) the first and/or the last record of a subject in a longitudinal setup. Normally in SAS one uses first.variable1 and last.variable1. So my question is that is there an R way of doing this. Regards, -- Luwis Diya, Phd student (Biostatistics), Biostatistical Center, School Of Public Health, Catholic University of Leuven, U.Z. St

Dear all, I would like to generate bi-variate normal data given that the first column of the data is known. for example: I first generate a set of data using the command, x <- rmvnorm(10, c(0, 0), matrix(c(1, 0, 0, 1), 2)) then I would like to sum up the two columns of x: x.sum <- apply(x, 1, sum) now with x.sum I would like to generate another column of data, say y, that makes

Hello, I need to subset my data to only look at the parts that have "holes" in it. I already have a formula to get rid of inconsistencies, but now I need to look only at the problem data to reconfigure it. In my data set where there are multiple "cycles" per "patient," and I want to highlight the patients who have a variable was not measured every cycle. Here's a

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

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,

Thanks for all the insightful responses that help me solve my problem. The original question is: how to call SAS from R The solution is as below: If my sas code, test.sas, is in directory c:\ncme06\sas codes, then the following codes works > system('"c:\\program files\\sas institute\\sas\\v8\\sas.exe" "c:\\ncme06\\sas codes\\test"') Things to notice: 1. need a

I am graphing longitudinal data from three time points. I'd like to draw a solid line from point 1 to point 2, and then a dashed line from point 2 to point 3. It works if I do it in two steps: > first.vector <- c(mean(year1$variable1), mean(year2$variable1)) > second.vector <- c(NA, mean(year2$variable1), mean(year3$variable1)) > plot(first.vector, type="b",

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 =

Hi, I have a dataset in which there are in all 250 variables and for each variable the data is entered over the months. I need to calculate the percentage of missing values for each variable over each month and then plot a graph for that. I am running the following code for doing the same *ds <- read.csv(file="filepath", header=TRUE) attach(ds) may <-

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

Dear R users, I tried to find a solution in the search list, but I cannot find it. I would like to read a .txt file with, let say, three variables, with two of which have repeated values in a number a columns. An example: The variables: Treat, x1, x2. The values: A 2.5 3.4 2.7 5.6 5.7 5.4 10.1 9.4 ... B 5.3 5.4 6.5 7.5 1.3 4.5 10.5 4.1 ... ... In the first column, the letters represent the

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, 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

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, 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, ",

Hello! one more question about xyplot. If I have data which have space in the column names, say "xyz 123". How do I create a working graph where this text is displayed in the legend key? Now when I try something like xyplot("xyz 123" ~ variable1, data = mydata, .......) I get nothing. Also, is it possible to genrate the graph with xyplot(mydata[,1] ~ variable1, data = mydata,