similar to: newbie: if statement with multiple conditions

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 =

Dear R experts, I would like to please ask for your help with repeating steps in an apply statement. I have a dataframe that lists multiple variables for a given id and visit, as well as drug treatment. > head(exp) id visit variable1 variable2 variable3 variable4 drug 1 3 1 13 10 7 11 0 2 3 5 10 15 9 9 0 3 3 12

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:

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 -

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

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

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",

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

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, I have a question about running multiple in regressions in R and then storing the coefficients. I have a large dataset with several variables, one of which is a state variable, coded 1-50 for each state. I'd like to run a regression of 28 select variables on the remaining 27 variables of the dataset (there are 55 variables total), and specific for each state, ie run a regression of

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, 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

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 ) ;

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,

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

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

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,

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