search for: score

...s like this { "_id" : ObjectId("4db8b0524f0b495c3a7dbba4"), "title" : "Testing1", "created" : ISODate("2011-12-12T00:00:00Z"), "tasks" : [ { "name" : "task no 1", "score" : "5" }, { "name" : "task no2", "score" : "6" } ] } { "_id" : ObjectId("4db8b0524f0b495c3a7dbba5"), "title" : "Testing2", "created" : IS...

...sted in hearing from others who need to do this kind of thing frequently. What approach do you use? Do you use one of the packages mentioned above? Are there other packages I might want to take a look at? Second question: I spent some time with the psych package trying to figure out how to use the score.items() function, and it's become clear to me that I don't understand what it's doing. I assumed that setting a key equal to -1 would result in the item being reverse scored, but I get weird results, as shown below. When I try to reverse score (by setting a value of -1 in the key), I ge...

...atter of practice. However, it seems the mapply function in this case is slower (in terms of CPU speed) than the for loop. Here is an example. # data needed for example items <- list(item1 = c(0,1,2), item2 = c(0,1), item3 = c(0,1,2,3,4), item4 = c(0,1), item5=c(0,1,2,3,4), item6=c(0,1,2,3)) score <- c(2,1,3,1,3,2) theta <- c(-1,-.5,0,.5,1) # My old function using the for loop like.mat <- function(score, items, theta){ like.mat <- matrix(numeric(length(items) * length(theta)), ncol = length(theta)) for(i in 1:length(items)) like.mat[i, ] <- pcm(theta, items[[i]], s...

Dear List! I am trying to calculate the distance between original data points and their position in the PLS model. In order to do this, I tried to predict the scores using the predict.mvr function and calculate the corresponding positions in variable space. The prediction of scores works perfectly: ------ data(trees) # build model t<-plsr(Volume~.,data=trees) # predict scores for training data and compare: # column 1: scores from model building # colu...

...omo Rnw, y luego puede ser corrido en R, donde seguramente al correr este se darán cuenta de mis dos problemas porque saltan al abrir el pdf que se obtiene como resultado. #################################3 código R #########################3 library(xtable) da <- data.frame(id=letters[1:5], score=1:5*2) col <- function(x){ ifelse(x>7, paste("\textcolor{blue}{", formatC(x, dig=2, format="f"), "}"), paste("\textcolor{red}{", formatC(x, dig=2, format="f"), "}")) } da$score.string <- col(da$score) xtable(d...

Hi everyone, I am trying to get the factor score for each individual case from a principal component analysis, as I understand, both princomp() and prcomp() can not produce this factor score, the principal() in psych package has this option: scores=T, but after running the code, I could not figure out how to show the factor score results. Here is...

...species, I have calculated the matrix of species distances using the Gower coefficient of similarity available in Package ?FD? (which allows missing values). My problem comes when I create a bi-plot of species and traits. As I have used a distance matrix in function ?metaMDS? there are no species scores available. This is given as a warning in R: "> NMDSgowdis<- metaMDS(SpeciesGowdis) > plot(NMDSgowdis, type = "t") Warning message:In ordiplot(x, choices = choices, type = type, display = display, :Species scores not available? I have read from internet resources that...

Hi, I'm new to R so please fogive if I write someting silly ... I need to recode a series of responses from a number of questionnaires. The data is read via ODBC from a database where all responses are coded as tables of the form (id, question, score). After dealing with recoding of missing values, I need to "invert" the scores of some questionnaire's item in the form x <- (n - x) where n is the range of allowed responses + 1, e.g. if score can range from 1 to 4 n would by 5. I am using R version 1.9.1 and 1.8.1 with identica...

Hi, I want to produce a pie chart with titles. I used the following code. So it created a pie chart for the percentage of the score for ID="002". ID <- c("001","001","002","002","002","003","003","003","004","004","005","005","006") test <- c("A","B","A&quot...

Hi, I have a data frame with 3 columns: ID, year and score. How can I select for each unique ID, the year that has the max score? For example, for data frame ID, year, score tom, 1995, 88 rick, 1994, 90 mary, 2000, 97 tom, 1998, 60 mary, 1998,100 I shall have ID, year, score tom, 1995, 88 rick, 1994, 90 mary, 1998,100 Thanks, Richard [[alternativ...

Dear all I'm unable to find an example of extracting the rotated scores of a principal components analysis. I can do this easily for the un-rotated version. data(mtcars) .PC <- princomp(~am+carb+cyl+disp+drat+gear+hp+mpg, cor=TRUE, data=mtcars) unclass(loadings(.PC)) # component loadings summary(.PC) # proportions of variance mtcars$PC1 <- .PC$scores[,1] # ext...

...hich is thought to have 11 factors. I can identify which factors the loadings relate to easily enough because I can see which items are loading onto each of the columns in the $loading output. However, how can I identify which items or loadings are being used to create each of the columns in the $scores output? I have used generalised linear models which have shown that some of the scores are significant predictors of treatment outcome, but I can't work out which of the 11 factors they are scoring? when I export to csv the $loadings I get the following columns in this order: MR4, MR3, MR2,...

Dear R experts: I have following data structure: student id, exam time and score. I want to create three new columes: 1 st before, 2nd before and 3rd before. For example, for student 1's 4th exam score is assumed to be influenced by his previous three cloest scores, which are 6, 9, and 10 in that order. For student 2's 5th exam score is assumed to be inflenced by her p...

The function factor.scores is used with package ltm and others to estimate IRT type scores for various models. It inherits objects of class grm, gpcm and a few others. What I would like to do is to use the factor.scores function, but feed it my own item parameters (from a bifactor model where the 2PL parameters are adjust...

I'm working with a data collected through complex survey design. My goal is to conduct a factor analysis to extract two a priori, known factors, and to get factor scores for these factors. Unfortunately, the "svyfactanal" procedure from the Survey package does not allow for the calculation of either Thompson regression scores or Bartlett scores. So, I found several sources that say one can simply sum "raw scores." I found this quote from this...

Dear all, I am trying to calculate a score for a string sequence consisting of the following four letters: ACGT. I have got a matrix giving the scores for each pair of letters. So for example the string ACCT has got the pairs: AC, CC and CT. The matrix has got the following form: names<-c("A","C","G",&quot...

...ndex::Index.new(:analyzer => MyAnalyzer.new()) index << { :content => "The quick brown fox" } index << { :content => "The cow jumps over the moon" } puts ''== Searching Brown...'' index.search_each(''content:Brown'') do |doc, score| puts "Document #{doc} found with a score of #{score}" end puts ''== Searching Foo...'' index.search_each(''content:Foo'') do |doc, score| puts "Document #{doc} found with a score of #{score}" end puts ''== Searching Brown...'...

...do the following, but i haven't been able to find it. I am hoping a merciful soul on R-help could point me in the right direction. I am doing a factor analysis on survey data with missing values. to do this, I run: FA1<-factanal(na.omit(DATA), factors = X, rotation = 'oblimin', scores = 'regression') Now that I have my factors and factor scores, I want to add those scores back to my original dataset so I can plot factor scores by demographics. However, when I try to add the scores back to the original data frame, the variables are of different lengths. Is there a...

Hi, I have a model tests_user and score which are associated with each other by has_one and belongs_to association. class TestsUser < ActiveRecord::Base has_one :score, :foreign_key => :reg_no end class TestsUser < ActiveRecord::Base belongs_to :tests_user, :foreign_key => :reg_no end where reg_no is a unique fiel...

Hello, I need help in performing a Van_der_Waerden normal scores test in R. I have two arrays of scores(final on therapy scores from drug and placebo) and want to use the normal scores procdeure to test for significance. (observations are unequal in number - due to dropouts). Could you please help me out with the coding or let me know if there is a package...