similar to: partial ranking models

Hello, it is likely that I will have to analyze a rather sizeable dataset: 60000 records, 10 to 15 variables. I will have to make descriptive statistics, and estimate linear models, glm's and maybe Cox proportional hazard model with time varying covariates. In theory, this is possible in R, but I would like to get some feedback on the equipment I should get for this. At this moment, I have a

dears, I like two write a program with R to estimate the coefficients of covariate,I like two know the original program for this programing for partial maximum likelihood for cox models with two co variate. I did it with coxph command, thanks [[alternative HTML version deleted]]

Hello, I am not very familiar with regular expressions and escaping. I need to replace the %-signs in a character vector with elements as "income 0%-33%# to be replaced by "income 0\%-33\%" (for later use in LaTeX). Using gsub("%","\\%","income 0%-33%") does not give the desired result. However, gsub("%","\\\\%","income

Hello all, I have just started using fitting the PCM (Partial Credit Model) using eRm and have 2 problems which I cannot solve, I have checked everywhere on the net, but no joy: Firstly, I have fit a PCM model to 10 variables with differing response categories (3 for the first 6 items, 4 for the following 2 and 2 for the last two items). mat1 <- matrix(c(rasch_bart$bart_bowel,

Hi All, a colleague asked me if R has a function producing a Partial Rank Correlation Coefficient, sensu Blower and Dowlatabadi 1994 [1]. I personally would not have a clue, and I could not find something like that on the search page... although I would not be surprised if it's there under a different name. Incidentally, unfortunately the function, assuming it exists, is to be fed to some

Hi, I am doing predictive modelling of Multivariate Time series Data of a Motor in R using various models such as Arima, H2O.Randomforest, glmnet, lm and few other models. I created a function to select a model of our choice and do prediction. Model1 <- function(){ .. return() } Model2 <- function(){ ... return() } Model3 <- function(){ ... return() } main <-

Hi, I'm trying to figure out how to have R estimate partial derivatives for logit models. As an example, I'm providing a (fake) scored observation in a MNL with 3 categories of Y and 2 predictors (x01 and x02), and show the right way to calculate it, but am looking for how to use an R function, such as deriv() or anything else. Here is my attempt: ### Variables for an observation x01

Dear all: I have a regression model that has collinearity problems (between three regressor variables). I need a F-test that will allow me to compare between full (with all variables) and partial models (minus 1=< variables). The general F-test formula I'm using is: F = {[SS(full model) - SS(reduced model)] / (#variables taken out)} / MSS(full model) Unfortunately, the ANOVA table

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Hey Everyone, Im fresh new in R, and Im supposed to write a code to give me a correlation between two rankings. So I have two ranking lists, which contain file names, e.g.: Ranking list 1: file1.java file3.java file2.java Ranking list 2: fiile2.java file4.java file1.java I need to see how much are these two ranking lists are alike, get a correlation between them. I dont even know where to

I have a small matrix where the columns represents a ranking and the values are the number of times each ranking was obtained eg 1 2 3 x 1 2 0 y 0 1 2 z 2 0 1 I'd like to be able to return an average of the ranking obtained average x 1.67 y 2.67 z 1.67 Whats the nicest way to do this? I'm new to the language and looking for an elegant solution :) Thanks Ben

Hi, I'm actually trying to rank a set of candidate models with an information criterion (AICc, QIC, BIC). The problem I have is that I use mixed-effect cox regression only available with the package {coxme} (see the example below). #Model1 >spring.cox <- coxme (Surv(start, stop, Real_rand) ~ strata(Paired)+R4+R3+R2+(R3|Individual), spring) I've already found some explications in

Hello, I want to discuss my idea on ranking in IR system which I think can be good extension to Xapian. If I am not too late to discuss it then please consider it. I first give you brief background of me, I am a Masters student working on my thesis in the Information Retrieval. I today only got a mail from one of the professor from Europe whom i am going to join for Ph.D about GSoC and more

Dear all, I'm working on ability estimates using Rasch model. Using the "ltm" package, the procedure is quite simple: ## Factor Scores for the Rasch model fit <- rasch(LSAT) factor.scores(fit) What about Partial Credit Model (PCM)? For PCM I use PCM function from eRm package. Is there any similar function like factor.scores to estimate ability scores using PCM model? Best,

Hi all, I am a biostatistician and I have developed my own ranking system for clinical data. I would like to test the efficiency of it w.r.t. to other ranking systems. I would like to simulate the data and after assigning ranks to my observed scores(after neglecting dropouts), observe the type I error. If I want to do a Kruuskal Wallis type of test, what test statistic should I use to test for a

Hello, I am afraid I do not fully understand all intricacies of programming in lattice plots. In the code below I try to plot an ROC curve, following R-news 4(1). When I condition on the variable 'group' I get the error message below, when I plot the curve for all data (i.e., y ~ pred.prob), I get the plot I want. Can someone point out why conditioning gives that message? Thanks, Ruud

Hello, I have estimated a survival model with six strata: >model.b <- survfit(Surv(time=start.tijd,time2=eind.tijd2,event=va)~strata(product.code) , data=wu.wide) I would like to save the output of >print(model.b,print.n="records",show.rmean=FALSE) in a dataframe so that I can export it later. How do I do this? Note that summary(model.b) gives an error: Error in

Hey Everyone, Im fresh new in R, and Im supposed to write a code to give me a correlation between two rankings. So I have two ranking lists, which contain file names, e.g.: Ranking list 1: file1.java file3.java file2.java Ranking list 2: fiile2.java file4.java file1.java I need to see how much are these two ranking lists are alike, get a correlation between them. I dont even know where to

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

Dear all, Are there any packages can estimate the partial linear model. Or any one can give me any suggestions. Many thanks in advance. Jin