similar to: Exact p-values in lm() - rounding problem

Dear R Mailinglist, I want to understand how predictors are associated with a dependent variable in a regression. I have 3 measurement points. I'm not interested in understanding the associations of regressors and the predictor at each measurement separately, instead I would like to use the whole sample in one regression, "pooling" the measurement points. I cannot simply throw them

I would like to obtain Confidence Intervals for the estimates (unstandardized beta weights) of each predictor in a WLS regression: m1 = lm(x~ x1+x2+x3, weights=W, data=D) SPSS offers that output by default, and I am not able to find a way to do this in R. I read through predict.lm, but I do not find a way to get the CIs for multiple independent variables. Thank you Torvon [[alternative HTML

We aim to visualize a 17*17 correlation matrix with the package *qgraph*, consisting of 16 variables. Without variable names in the input file, that works perfectly R> qgraph(data) but we'd like variable names instead of numbers for variables. In a correlation matrix, the first row and the first column usually have variable names. We've been unsuccessful so far to read such a file

I have two regressions to perform - one with a metric DV (-3 to 3), the other with an ordered DV (0,1,2,3). Neither normal distribution not homoscedasticity is given. I have a two questions: (1) Some sources say robust regression take care of both lack of normal distribution and heteroscedasticity, while others say only of normal distribution. What is true? (2) Are there ways of using robust

I am intersted in time-space clustering of local industry. I made the point file, polygons and time table then run 'stkhat' function in Splancs, but it generates only time k function. I noticed that it has only one ks value. ... Can anybody help me?. thanks in advance. countiespt <- read.table('d:/dissertation/dailynew/jun10/countiespt_ok.txt', sep=",")

How for the love of god can I prevent the lm() function from padding on to my factor variables? I start out with 2 tables: Table1 123123 124351 ... 626773 Table2 Count,IS_DEAD,IS_BURNING 1231,T,F 4521,F,T ... 3321,T,T Everything looks fine when I import the data. then we get a oh_crap <- lm(table1 ~ Count + IS_DEAD + IS_BURNING, table2) Magically when I look at my oh_crap coefficents

Dear R users, Just to clarify. I am not offering to pay someone to do my Dissertation. These 4-5 commands on Kalman Filter would be only a tiny part of my 10,000 words dissertation. A part that even after trying for a few days, I am still stuck on. I am offering ?50, just to say thanks. Regards -- View this message in context:

I''m using a plugin which adds a method to ActiveRecord::Base http://similetimelinerailshelper.googlecode.com/svn/trunk/simile_timeline/ This adds an "acts_as" type declaration to the Models, via the file in vendor/plugins/simile_timeline/lib/simile_timeline.rb Rails is working with these declarations, and they are being used successfully in ''regular

I have two very strong fixed effects in a LMM (both continuous variables). model <- lmer( y ~ time + x1+x2 + (time|subject)) Once I fit an interaction of these variables, both main effects disappear and I get a strong interaction effect. model <- lmer( y ~ time + x1*x2 + (time|subject)) I would like to plot this effect now, but have not been able to do so, reading through ggplot2 and

Hello, I am trying to add R code to my dissertation and the length of a line of text that Sweave generates is longer than the right margin in my dissertation. I have found no way to tell Sweave how to set the line length. I am using an iMac with tiger ver. 10.4.10, and R: ver. 2.5.1. Here is the R code that is longer than my right margin: input to Sweave:

Hey Everyone, I wrote up a library for my dissertation work, and I'd love to include it as an appendix. I have found ways to export the Rd files as html, txt and pdf/ps, but not a raw tex export. I've had to resort to dumping it into text files, and just using verbatim in my LaTeX code. Does anybody have any recommendations or experiences with dealing with this? Please CC me on

I am running 9 negative binomial regressions with count data. The nine models use 9 different dependent variables - items of a clinical screening instrument - and use the same set of 5 predictors. Goal is to find out whether these predictors have differential effects on the items. Due to various reasons, one being that I want to avoid overfitting models, I need to employ identical types of

Hi all, Suppose: y<-rnorm(100) x1<-rnorm(100) lm.yx<-lm(y~x1) To predict from a new data source, one can use: # works as expected dum<-data.frame(x1=rnorm(200)) predict(lm.yx, newdata=dum) Suppose lm.yx has been run and we have the lm object. And we have a dataframe that has columns that don't correspond by name to the original regressors. I very! naively assumed that doing

Hi all ! I've just finished my Master's dissertation of Political Science about FOSS. In the third chapter i used of examples of Samba community. That is the reason why i want to share this with you and you might find the text at the following addresses : in portuguese : http://bit.ly/2Egkbv in french : http://bit.ly/2VJLPp It was quite difficult for me to talk about technology and

to clean up some code I would like to make a list of arbitrary length to store?various objects for use in a loop sample code: ############ BEGIN SAMPLE ############## # You can see the need for a loop already linearModel1=lm(modelSource ~ .,mcReg) linearModel2=step(linearModel1) linearModel3=lm(modelSource ~ .-1,mcReg) linearModel4=step(linearModel3) #custom linearModel5=lm(modelSource ~ .

Hello, I am trying to read in an Excel file that I saved as a .csv so I can analyze my dissertation data! I am getting really frustrated because this is what I keep getting: In read.table(file = file, header = header, sep = sep, quote = quote, : incomplete final line found by readTableHeader on 'month.csv' can anyone offer some help? Thanks a lot! catherine [[alternative HTML

I have a situation with a large dataset (3000+ observations), where I'm doing lags as regressors, where I get: Call: lm(formula = rj ~ rM + rM.1 + rM.2 + rM.3 + rM.4) Residuals: 1990-06-04 1994-11-14 1998-08-21 2002-03-13 2005-09-15 -5.64672 -0.59596 -0.04143 0.55412 8.18229 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) -0.003297 0.017603

Dear useRs: Is there a way to include a raster image (e.g., .gif, .jpg, .bmp) representing a company logo, a school logo, etc. into an R graphic? For example, it would be nice to be able to include the logo of the school into the charts that a student produces for her dissertation. Similarly, while working on a competitive analysis, it would be nice to be able to replace the names of the

I am reading regressors from an excel file (I have no control over the file) and some of the element names have spaces: i.e. "Small Bank Aquired" but I have found that lm(SourceData ~ . - "Small Bank Aquired", mcReg) doesn't work (mcReg = modelCurrentRegressors) As they are toggles I have ran them through factor() to be treated propertly as 0 or 1 but due to the fact I

The model matrix for the code at the end the email is shown below. Since the model matrix doesn't have -1, I think that it is made of dummy regressors rather than deviation regressors. I'm wondering how to make a model matrix using deviation regressors. Could somebody let me know? > model.matrix(aaov) (Intercept) A2 B2 B3 A2:B2 A2:B3 1 1 0 0 0 0 0 2