similar to: Hierarchical Regression

Howdy! Could somebody point me to some good introductory readings about data mining and descriptive data analysis? I'm a psychologist and a couple of times I realized that some things just don't appear in psychological literature, e.g. I've never seen a box plot anywhere in psych journals so I'm not familiar with them. The R help function is great when it comes to explaining

Howdy! Has anybody successfully installed R under OpenBSD? I just tried to install the latest R-release under OpenBSD 2.7 and got the following errors in the make step: pnorm.c:62 'ML_ERR_return_NAN' undeclared pnorm.c:62 'ML_NAN' undeclared pnorm.c:62 'ML_NEGINF' undeclared --Ragnar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help

Howdy! Has anybody successfully installed R under OpenBSD? I just tried to install the latest R-release under OpenBSD 2.7 and got the following errors in the make step: pnorm.c:62 'ML_ERR_return_NAN' undeclared pnorm.c:62 'ML_NAN' undeclared pnorm.c:62 'ML_NEGINF' undeclared --Ragnar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help

Hi, I'm trying to build a hierarchical logistic regression model with lme4 package, but I have a problem on selecting the variables to include in this model. In a simple logistic regression, using Forward selection, i use a likelihood ratio test to check which variables i should include in the model, using the function add1(). The problem is that this function doesn't work with the

Dear R Help, I have noticed some inconsistent behaviour of add1 and drop1 with a weighted linear model, which affects the interpretation of the results. I have these data to fit with a linear model, I want to weight them by the relative size of the geographical areas they represent. _________________________________________________________________________________________ > example

Is there a way to automate fitting and assessing loglinear models for several nominal variables . . . something akin to step or drop1 or add1 for linear or logistic regression? Thanks. --Chris -- Christopher W. Ryan, MD SUNY Upstate Medical University Clinical Campus at Binghamton 40 Arch Street, Johnson City, NY 13790 cryanatbinghamtondotedu "If you want to build a ship, don't drum

Hello, I am trying to obtain f-values for response (independent) variables from a CCA performed in vegan package, to see which ones of them have significative influence in my dependent variables (like the manual selection in canoco), but I can't find any function (or package) that do such a thing. The dependents variables are species data, and the independents are ambiental data. Than you.

Howdy, I looked at the references in the R and S-Plus literature to find a good introduction/reference to GLM. When I then went to Amazon it seemed to me that all the recommended books are out of print. Can anyone give me a recommendation which _available_ book to get? --Ragnar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I've been poking around with GLMs (on which I am *not* an expert) on behalf of a student, particularly binomial (standard logit link) nested models with overdispersion. I have one possible bug to report (but I'm not confident enough to be *sure* it's a bug); one comment on the general inconsistency that seems to afflict the various functions for dealing with overdispersion in GLMs

Hello all, I have a question on manova in R: I'm using the function "manova()" from the stats package. Is there anything like a stepwise (backward or forward) manova in R (like there is for regression and anova). When I enter: step(Model1, data=Mydata) R returns the message: Error in drop1.mlm(fit, scope$drop, scale = scale, trace = trace, k = k, : no 'drop1'

Dear all, I have been trying to investigate the behaviour of different weights in weighted regression for a dataset with lots of missing data. As a start I simulated some data using the following: library(MASS) N <- 200 sigma <- matrix(c(1, .5, .5, 1), nrow = 2) sim.set <- as.data.frame(mvrnorm(N, c(0, 0), sigma)) colnames(sim.set) <- c('x1', 'x2') # x1 & x2 are

Hi, I am wondering if anyone knows how to perform an F-test on the change in R square between hierarchical models in R? SPSS provides this information and a researcher that I am working with is interested in getting this information. Alternatively, if someone knows how I can calculate the test statistic (SPSS calls it F-change?) and dfs that would be helpful as well. The output and the test I am

Howdy! I'm trying to print a correlation matrix where every r is rounded to two digits after the colon. How can I get that? I tried options(digits=2) but that rather yields two digits minimum precision so that I get 0.0068 instead of 0.01. Ragnar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

I am hoping to get some advise on the following: I am looking for an automatic variable selection procedure to reduce the number of potential predictor variables (~ 50) in a multiple regression model. I would be interested to use the forward stepwise regression using the partial F test. I have looked into possible R-functions but could not find this particular approach. There is a function

Dear all R users : I am a IT student with few statistical background and new R user for only have two month exprience. I have a data named medcost, import by read.table() as follow for example (real dataset has 500 cases), the heander id means case id, member means members in a family and cost is the family pay for medical cost every 6 months. id member cost 1 4

Howdy! I have a problem that's similar to one discussed earlier on the list: When not in xterm all the backspace and cursor-movements and stuff are working well. Only when I start R in an xterm window backspace appears as ^H and so on. What can I do? Ragnar -.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.-.- r-help mailing list -- Read

Dear All, I have a problem understanding the difference between the outcome of a fisher exact test and a chi-square test (with simulated p.value). For some sample data (see below), fisher reports p=.02337. The normal chi-square test complains about "approximation may be incorrect", because there is a column with cells with very small values. I therefore tried the chi-square with

i have search the web and not find code to cal these index.so i write one.if there exists code for such index,i hope you can let me know. this is my first R code.i send the the list and hope uesRs give me some advise for improve it or check if i make any mistake . i appriciate your suggestion . i have check the result roughly to the SPSS's. though i do not know excatly how SPSS calculate the

Subject: Eliminate repeated components from a vector X-Mailer: VM 7.00 under 21.4 (patch 6) "Common Lisp" XEmacs Lucid Reply-To: fjmolina at lbl.gov FCC: /home/f/.xemacs/mail/sent Does anyone know how I can eliminate repeated elements from a vector?

In RW0.651 and RW0.901, I discovered some unexpected behaviour when I used as.matrix.data.frame() > matrix('"', 2, 2) [,1] [,2] [1,] "\"" "\"" [2,] "\"" "\"" > unclass(as.data.frame(matrix('"', 2, 2))) $V1 [1] "\"" "\"" $V2 [1] "\"" "\""