similar to: Plot with Group # as pch

I have a data file with indicates pretest scores for a linguistics experiment. The data are in long form so for each of 33 subjects there are 400 rows, one for each item on the test, and there is a column called ‘Correct’ that shows ‘C’ for a correct response and ‘E’ for an incorrect response. I am trying to write a formula that will create a vector that indicates the number of correct answers

Dear All, I have a list of models(1000) which have variable scores from 20 different method. I would like to rank models using consensus approach based on high scores from different methods.Is there any function available in R for this purpose? I will appreciate any pointers in this regard. Thank you very much in Advance, Mallika

I am trying to import a series of text files generated by stimulus presentation software. The problem that I am having is that the number of rows I need to skip is not fixed (depending on subject's pretest behavior) nor is the first row of the data I want always the same (the stimuli were presented in random order). So I need to bring in the .txt file (using readLines?), look for the row

HI All, I have a long data file generated from a minimal pair test that I gave to learners of Arabic before and after a phonetic training regime. For each of thirty some subjects there are 800 rows of data, from each of 400 items at pre and posttest. For each item the subject got correct, there is a 'C' in the column 'Correct'. The line: tapply(ALLDATA$Correct,

I would like to fit the following function on my data. out.nls<-nls(z ~ p1+ (p2*dat)+(p3*dat^2)+(p4*dat^3)+(p5*AgeS)+(p6*AgeS^2)+(p7*AgeS^3)+ (p8*(dat*AgeS))+(p9*(dat^2*AgeS))+(p10*(dat^3*AgeS))+ (p11*(dat*AgeS^2))+(p12*(dat*AgeS^3))+(p13*(dat^2*AgeS^2))+ (p14*(dat^2*AgeS^3))+(p15*(dat^3*AgeS^3)),

Hello all, An elementary question that I am sure can be easily cracked by an R enthusiast. Let's say I have multiple scores (y) on subjects (x.sample). Some subjects have a few more scores than others. Can somebody suggest some code that will select the first score for each subject? For example, the following code generates scores for 5 subjects: > x <- c(1:5) > x.sample <-

Hello, I have some data in a data.frame where for each of a number of subjects, I have scores for all of a number of symptoms. Subjects are subdivided in a number of groups, which have unequal sizes. I'd like to plot between-group differences in the scores on the various symptoms. Ideally, that would be in a form as would be produced by > bwplot( Score~Symptom ) but I'm not sure

I have a slight conundrum. I'm attempting to write a scrip that will take a number of objects (lm, glm, and lmer) and return AIC scores and weights. I've run into 3 problems, and was wondering if anyone had any pointers. 1) is there any convenient way to extract the name of the objects? Simply, if I have a vector of objects c(my.lm, my.lmer) and I want to get a character

How can I get the outlier in this boxplot of "Score" to be represented by the corresponding value in "SubNo"? score=c(6,6,7,14,5,7,6,8) SubNo=1:8 mydata=data.frame(SubNo, score) boxplot(mydata$score) Thanks! Kevin [[alternative HTML version deleted]]

Dear All, I have a data as follows: ID <- 1:100 Y <- rnorm(100) X <- rnorm(100) type <- as.factor(rep(1:3,100,time=1)) df <- as.data.frame(cbind(ID, Y,X,type)) I want to plot Y versus X by specifying the pch to be as follows: Subjects having type = 1 must be plotted with a character pch = "A" Subjects having type = 2 must be plotted

Does anyone know if the lmer function of lme4 works fine for unbalanced designs? I have the examination results of 1000 pupils on three subjects, one score every term. So, I have three scores for English (one for every term), three scores for maths etc. However, not everybody was examined in maths, not everybody was examined in English etc, but everybody was in effect examined on four subjects. I

Hi my friends, I have an issue with ability estimates when running GRM of IRT. I have responses from 242 subjects but got 183 ability estimates. Below is what I did to get the estimates. 1) I have a csv file "P1.csv" and I imported it into R and loaded the "ltm" package by doing: p1<-read.table("P1.csv",header=TRUE,sep=",") library(ltm) 2) I

Hi, I have a series of id's with multiple visits and questionnaire scores. This is a clinical trial that will be analyzed using the last observation carried forward method. In other words, in order to comply with intent to treat analysis when many subjects withdraw, data points for the last visit must be generated and filled in with the last observation. The ultimate goal is to tabulate the

Hello, I've got what I'd expect to be a pretty simple issue: I fit an aov object using multiple error strata, and would like some significance tests for the contrasts I specified. In this contrived example, I model some test score as the interaction of a subject's gender and two emotion variables (angry, happy, neutral), measured at entry to the experiment (entry) and later

Hi All, I have been trying to get to plot my PCA legend outside of the PCA plot, but success still alludes me. Can you guys please advise how I can achieve this. I used locater() to obtain coordinates for below the Comp.1 axis. Using these coordinates the legend disappears. Below is the code for the PCA and legend. Thanks in advance for the help. Regards Tinus r.cols <-

Hi, I am running a Cox Mixed Effects Hazard model using the library coxme. I am trying to model time to onset (age_sym1) of thought problems (e.g. hearing voices) (sym1). As I have siblings in my dataset, I have decided to account for this by including a random effect for family (famid). My covariate of interest is Mother's diagnosis where a 0 is bipolar, 1 is control, and 2 is major

I have the following script for generating a dataset. It works like a champ except for a couple of things. 1. I need the variables "itbs" and "map" to be negatively correlated with the binomial variable "lunch" (around -0.21 and -0.24, respectively). The binomial variable "lunch" needs to remain unchanged. 2. While my generated variables do come out

Hi, I am currently analysis Raman spectroscopic data with the hyperSpec package. I consulted the documentation on this package and I found an example work-flow dedicated to Raman spectroscopy (see the address : http://hyperspec.r-forge.r-project.org/chondro.pdf) I am currently trying to remove outliers thanks to PCA just as they did in the documentation, but I get a message error I can't

Hi there, I am plotting relative warp scores (equivalent to pca scores) and I want to label (color code and shape) the points by group. I can't figure out how to do this beyond simple plotting. plot(RW1, RW2); Do I need to make vectors of each group and then plot them separately onto the same plot? How do I go about this? Thanks! -- View this message in context:

Hi everyone, I'm sure this is simple, but I can't seem to figure this out. Situation. 3 different groups of subjects each submit n X n matrices of scores. What I want to do is aggregate each group of scores into a summary n X n matrix. I need the result to be a matrix so that I can calculate a dissimilarity structure on it. So I thought I would create a multi-dimensional array and