similar to: Restructure some data

Greetings, I'm learning R and I'm stuck on a basic concept: how to specify a logical condition once and then perform multiple transformations under that condition. The program below is simplified to demonstrate the goal. Its results are exactly what I want, but I would like to check the logical state of gender only once and create both (or any number of) scores at once.

hi all - i'm having trouble using lme to specify a mixed effects model. i'm pretty sure this is quite easy for the experienced anova-er, which i unfortunately am not. i have a data frame with the following columns: col 1 : "Score1" (this is a continuous numeric measure between 0 and 1) col 2 : "Score2" (another continuous numeric measure, this time bounded between 0

Hi, all. I'd like to add legend on my graph but I can't. My code is follows. library(ggplot2) score1<-rnorm(100,0,5) score2<-rnorm(400,10,15) mydata<-data.frame(score1,score2) ggplot(mydata,aes(y=score2,x=score1))+geom_point()+stat_quantile(quantiles=c(0.50),col="red")+stat_quantile(quantiles=c(0.90),col="blue",size=2) I like to add legend indicating the

Dear colleagues, I have a problem which has bitten me occasionally. I often need to prepare graphs for many variables in a data set, but seldom for all. or for any large number of sequential or sequentially named variables. Often I need several graphs for different subsets of the dataset for a given variable. I run into similar problems with other needs besides graphing. What I would like to

Dear R-Users, I have a big data set "mydata" with repeated observation and some missing values. It looks like the format below: userid sex item score1 score2 1 0 1 1 1 1 0 2 0 1 1 0 3 NA 1 1 0 4 1 0 2 1 1 0 1 2 1 2 NA 1 2 1 3 1

Hi I'm hoping someone can help me I am a relative newbie to R. I have data that is in a similar format to this... Experiment Score1 Score2 X -0.85 -0.02 X -1.21 -0.02 X 1.05 0.09 Y -1.12 -0.07 Y -0.27 -0.07 Y -0.93 -0.08 Z 1.1 -0.03 Z 2.4 0.09 Z -1.0 0.09 Now I can easily have a look at the overall correlation of score 1 and 2 by doing this plot(data[,2], data[,3]) or fit <-

Dear List: A few weeks ago I posted some questions regarding data simulation and received some very helpful comments, thank you. I have modified my code accordingly and have made some progress. However, I now am facing a new challenge along similar lines. I am attempting to simulate 250 datasets and then run the data through a linear model. I use rm() and gc() as I move along to clean up the

I'm an R novice and my colleagues are about to convince me to get my data into SPSS, which will presumably be easier for someone who doesn't live in R to point and click his way into some kind of analysis that might be meaningful. I've got two groups of subjects (classkey in the table below). They've each received several different treatments. One measure is a 1-7 rating taken

I am new to R and have tried for a good while to figure out how to code this in R. The dataset below: FTIStandKey State County FTITract CoverType Ver_CT V_Origin V_SpGrp NAH6005-001 Texas Jasper NAH6005 PPLB-2000-U PPLB-2000-U P P NAH6005-002 Texas Jasper NAH6005 NHHX-1950-O NHHX-1950-I N H NAH6253-001 Texas Tyler NAH6253 PPLB-2001-U PPLB-2001-U P P

Dear List: I am running into a memory issue that I haven't noticed before. I am running a simulation with all of the code used below. I have increased my memory to 712mb and have a total of 1 gb on my machine. What appears to be happening is I run a simulation where I create 1,000 datasets with a sample size of 100. I then run each dataset through a gls and obtain some estimates. This works

Hello R users, I'd like to ask a question about how to add a new column. So, below is my situation. In order to perform the repeated ANOVA, I first imported the following table. score=read.csv("patients_tests.csv"); subject test1 test2 test3 test4 test5 test6 test7 1 ab 0.17687 0.16715 0.17009 0.16480 0.16116 0.24502 0.17975 2 cl

List: Thank you for the replies to my post yesterday. Gabor and Phil also gave useful replies on how to improve the function by relying on mapply rather than the explicit for loop. In general, I try and use the family of apply functions rather than the looping constructs such as for, while etc as a matter of practice. However, it seems the mapply function in this case is slower (in terms of CPU

I am new to R and have tried for a good while to figure out how to code this in R. The dataset below: FTIStandKey State County FTITract CoverType Ver_CT V_Origin V_SpGrp NAH6005-001 Texas Jasper NAH6005 PPLB-2000-U PPLB-2000-U P P NAH6005-002 Texas Jasper NAH6005 NHHX-1950-O NHHX-1950-I N H NAH6253-001 Texas Tyler NAH6253 PPLB-2001-U PPLB-2001-U P P

I think I am overlooking a call or concept in R to help me easily and quickly restructure my data.frame:   Sometimes the data I receive looks like: VariableName, Run1, Run2, Run3, Location temp,               15.0,  16.0,  17.0, There   And other times it looks like: VariableName, Run, Location temp,               17.0, There   I would like to use the header information in order to be able to

Dear friends, In S-PLUS, we can use the following argument, but not in R. mode12 <- gam(score1 ~ lo(latitude) + lo(longitude)) I searched the help in S-PLUS, it says lo() Allows the user to specify a Loess fit in a GAM formula, but i didn't find the correponding function in R. Anybody knows how to do the similar task in R? Thanks very much. -- With Kind Regards, oooO:::::::::

Hi Everyone, I've got a question about data representation. I have some psychometric data with 5 scores for 15 different groups. I've been asked to show some kind of mean plots. The data below is the mean and SD for a given group, unfortunately my employer doesn't want me posting full datasets. :( The groups V,W,X,Y,Z are divided into Bottom, (B), Middle (M) and Top (T). An

From: Gene Cumm <gene.cumm at gmail.com> COM32 API: restructure DIR to include a dirent to eliminate the need for alloc()/free() of dirents Signed-off-by: Gene Cumm <gene.cumm at gmail.com> --- Counted incorrectly. Depends on previous patches. diff --git a/com32/include/dirent.h b/com32/include/dirent.h index 5161828..a544050 100644 --- a/com32/include/dirent.h +++

restructure try_release_extent_buffer() and write a function to release the extent buffer. It will be used later. Signed-off-by: Miao Xie <miaox@cn.fujitsu.com> --- fs/btrfs/extent_io.c | 48 +++++++++++++++++++++++++++++++++++++----------- 1 files changed, 37 insertions(+), 11 deletions(-) diff --git a/fs/btrfs/extent_io.c b/fs/btrfs/extent_io.c index 41277d6..70b7cc5 100644 ---

Hi all, Now that there is an effort underway to improve the look/theme of the Wiki. I would like to discuss the content of the wiki. IMO there are too many links on the frontpage. With a new theme, the News/Events items on top can go into a sidebar, so that will be taken care of the news items. I will not discuss them here. But currently, there is little structure in all the links/titles on the

Dear List: I have a question regarding an MDS procedure that I am accustomed to using. I have searched around the archives a bit and the help doc and still need a little assistance. The package isoMDS is what I need to perform the non-metric scaling, but I am working with similarity matrices, not dissimilarities. The question may end up being resolved simply. Here is a bit of substantive