similar to: summary.glm() print problem(?) with cor = TRUE

Hello, I am trying to export the results from symnum() while maintain their readability. I tried using sink to text file and also copying and pasting but the results end up looking like this: > symnum(c5.s) bC bED bEN bLP bLS bPA bPD bPR p bbContag 1 bbED + 1 bbENN_MN + B 1 bbLPI , , , 1 bbLSI + B B , 1 bbPAFRAC , * * , * 1 bbPD , B B

This is a question about removing the intercept in a binomial glm() model with categorical predictors. V&R (3rd Ed. Ch7) and Chambers & Hastie (1993) were very helpful but I wasn't sure I got all the answers. In a simplistic example suppose I want to explore how disability (3 levels, profound, severe, and mild) affects the dichotomized outcome. The glm1 model (see below) is

Hi all, In a simulation context, I'm applying some my function, "myfun" say, to a list of glm obj, "list.glm": >length(list.glm) #number of samples simulated [1] 1000 >class(list.glm[[324]]) #any component of the list [1] "glm" "lm" >length(list.glm[[290]]$y) #sample size [1] 1000 Because length(list.glm) and the sample size are rather large,

Hello, Is there a way to put multiple data.frames or objects into a single .csv ? I know I can use sink() to do this for a text file. Is there way to do it for a .csv? e.g. for sink() sink("c5.k.s.p.92.LN.sl.vs.mean.txt") symnum(c5.k.92.LN.sl.vs.mean) symnum(c5.s.92.LN.sl.vs.mean) symnum(c5.p.92.LN.sl.vs.mean) sink() Could I put these all into a single .csv, in a similar format to

Hi, I apologize if the solution is right in front of me, but I can't find anything on how to convert a class of 'noquote' to 'matrix'. I've tried as.matrix and I've tried coercing it by 'class(x)<-matrix', but of course that didn't work. I've been using the function 'symnum' which returns an object of class 'noquote'. Here is an

This is a question regarding the 'regTermTest' function in the 'survey' package. Imagine Z as a three level factor variable, and code ZB and ZC as the two corresponding dummy variables. X is a continuous variable. In a 'glm' of Y on Z and X, say, how do the two test specifications test.terms = c("ZB:X","ZC:X") # and test.terms = ~ ZB:X + ZC:X in

Okay, I stumped. I'm trying to build a matrix or data.frame that consists of values by group. For example, resid, group 574 0.536196370873122 E 575 0.93191093696265 E 576 -1.27116094894117 A 577 -1.05159666055027 A 578 0.398273458301184 D 579 0.586373126102573 E 580 0.806575304513802 E 581 0.897258393118338 E 582 0.342393324256838 D 583 0.781245511773227 E I

Hi all I'm getting a NaN returned on using dffits, as explained below. To me, there seems no obvious (or non-obvious reason for that matter) reason why a NaN appears. Before I start digging further, can anyone see why dffits might be failing? Is there a problem with the data? Consider: # Load data dep <-

Dear R-List users, Can anyone explain exactly the difference between Weights options in lm glm and gls? I try the following codes, but the results are different. > lm1 Call: lm(formula = y ~ x) Coefficients: (Intercept) x 0.1183 7.3075 > lm2 Call: lm(formula = y ~ x, weights = W) Coefficients: (Intercept) x 0.04193 7.30660 > lm3 Call:

R 2.3.1 I wrote a little script to do some cross correlations. The symbols are in a text file like so: symbols.txt ibm dd csco """ require(tseries) symbols <- scan("symbols.txt", what = 'character') for(line in 1:(length(symbols)-1)) { assign(symbols[line], get.hist.quote(instrument = symbols[line], start = "2005-09-01", quote =

Dear List, I have a large (1600*1600) matrix generated with symnum, that I am using to eyeball the structure of a dataset. I have abbreviated the column names with the abbr.colnames option. One way to get an even more compact view of the matrix would be to display the column names rotated by 90 degrees. Any pointers on how to do this would be most useful. Any other tips for displaying the

Hi all, Does anyone know a way to change the significant stars in mtable (package memisc)? The default is Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1, however I need it to be Signif. codes: 0 '***' 0.01 '**' 0.05 '*' 0.1 ' ' 1 Kind regards, Erich [[alternative HTML version deleted]]

Hi there, I got a piece of code for the Iris data which allows to display correlation coefficients for each Iris species in the lower panel (color coded). I would now like to add e.g. a "*" to show the significance of each correlation next to the correlation coefficient. Furthermore I would like to make a t.test between the species "setosa" and "versicolor" for

Dear r-help users, I am using Sweave and Latex to create tables with output from several statistical test. As an example: I have a grouping variable "group" with two levels ("x" and "y") which I compare on variables ("a" and "b"). I have created a table in which means, standard deviations, and the statistic and p.value resulting from a t.test is

I was hoping that there might be some way to attach significance code like the ones from summary.lm to a dataframe. Anyone know how to do something like that. Here is the function i'd like to add that functionality to: add1.coef <- function(model,scope,test="F",p.value=1,order.by.p=FALSE) { num <- length(model$coefficients) add <- add1(model,scope,test=test) sub <-

R-folks, Is there a function, like aggregate, that allows users to bin values? I've got to break down a data frame into classes of 5cm (or something like it), and I only know how to do it using code like, signif <- symnum( stems$dbh, corr = FALSE, na = FALSE, cutpoints = c(0,10,20,30,40,999), symbols = c(0,10,20,30,40) )

Hello, I'd like to add custom labels to my pair() plot. These labels include math expression but they aren't correctly displayed... Further, I want that the boxes for the text.panel (diagonal) have an other background color (grey80). Is that generally possible? If yes how do I have to set it? What I've so far is: panel.cor <- function(x, y, digits=2, prefix="",

Dear List, I am looking to perform exploratory analyses of two (relatively) large datasets of categorical data. The first one is a binary 80x100 matrix, in the form: matrix(sample(c(0,1),25,replace=TRUE), nrow = 5, ncol=5, dimnames = list(c( "group1", "group2","group3", "group4","group5"), c("V.1", "V.2", "V.3",

I've trying to check for model bias. It was recommended to me that I should break the residuals into n groups and test to see if the mean is different from zero. What is the best way to generate the groups. I've generated a matrix that contains the residuals and groups, but the values all have quotes around them. 1) how do I get rid of the quotes? 2) is this an acceptable method for

The document R-exts contains the following example of using mathematics in R documentation. \deqn{p(x) = {\lambda^x\ \frac{e^{-\lambda}}{x!}} {p(x) = lambda^x exp(-lambda)/x!} There is a syntax error in there, but that's not my point. The problem is that using "R CMD Rd2dvi" I find that putting the alternate forms of the equation on top of each other doesn't work.