similar to: 3-way interaction simple slopes

I would appreciate some thoughts on using the bootstrap functions in the library "bootstrap" to estimate confidence intervals of ICC values calculated in lme. In lme, the ICC is calculated as tau/(tau+sigma-squared). So, for instance the ICC in the following example is 0.116: > tmod<-lme(CINISMO~1,random=~1|IDGRUP,data=TDAT) > VarCorr(tmod) IDGRUP = pdLogChol(1)

Hi everyone, I'm sure this is pretty basic but I couldn't find a clear example of how to do this. I'm running a regression, say: reg <- lm(Y ~ x1 + year) where x1 is a continuous variable and year is a factor with various year levels. Individually, each year factor variable is not significant, but I have a suspicion they are jointly significant. I can't figure out how to run

Forgive me if this is a trivial question, but I couldn't find it an answer in former forums. I'm trying to reproduce some SAS results where they set two parameters equal. For example: y = b1X1 + b2X2 + b1X3 Notice that the variables X1 and X3 both have the same slope and the intercept has been removed. How do I get an estimate of this regression model? I know how to remove the intercept

I am working with a RCB 2x2x3 ANCOVA, and I have noticed a difference in the calculation of sum of squares in a Type III calculation. Anova output is a follows: > Anova(aov(MSOIL~Forest+Burn*Thin*Moisture+ROCK,data=env3l),type=3) Anova Table (Type III tests) Response: MSOIL Sum Sq Df F value Pr(>F) (Intercept) 22.3682 1 53.2141 3.499e-07 *** Forest

Re-sending, since I forgot to include the list, sorry. I'm including r-package-devel too this time, as it seems more appropriate for this list. El 22 ene. 2018 10:11, "I?aki ?car" <i.ucar86 at gmail.com> escribi?: > > > El 22 ene. 2018 8:12, "Ulrich Bodenhofer" <bodenhofer at bioinf.jku.at> > escribi?: > > Dear colleagues, dear members of

For some time I have been looking for a convenient way of performing post-hoc analysis to Repeated Measures ANOVA, that would be acceptable if sphericity is violated (i.e. leaving aside post-hoc to lme models). The best solution I found was John Fox's proposal to similar requests in R-help: http://tolstoy.newcastle.edu.au/R/e2/help/07/09/26518.html

Hi folks - I'm having an issue here. I have my samba server sitting on one subnet, and the rest of the clients sitting on another (due to IP administration reasons). I assign both my clients and the server to the same workgroup, but the winboxen clients can't browse to the samba server. The win clients all have WINS resolution turned on, and I specified all of my WINS servers in

Everyone, I am looking for a utility that I can use to do a mail merge of data to a pdf image file. The image file does not have any active fields, but will be just an image file. I would like to overlay names addresses etc. We currently do this with a pcl file by just overlaying the data with pcl print positions. However, in order to get the pcl file from an original pdf file we have to

Hi All, I am confused with SMATR's test for common slope. My null hypothesis here is that all slopes are parallel (common slopes?), right? So if I get a p value < 0.05 means that we can have confidence to reject it? That slopes are different? Or the other way around? it means that we have statistical confidence that the slopes are parallel? thanks -- Eugenio Larios PhD Student University

Dear all If I run the model and get the estimated parameter a11. Then I want to use the estimated parameter to calculate the elasticities by using the formula e11=a11/mw1-1. What I have done is using the command of linear. Hypothesis. > formulas1=dWfresh~dlnPfresh+dlnPfrozen+dlnPsmoke+dlnQP+cosL1+sinL1+cosL2 >

Everyone, I am currently using a vsifax program (pcltotiff) to convert pcl files to tiff files on a SCO Unix box, and then I am using tiff2pdf on a Centos 5.9 box to convert the file to a pdf. There are other commands that deal with multiple page tiff's and pdf's that are part of the process, but the above basic process has worked very well. The only thing I would like to enhance is a

Hi, I'm trying to get confidence intervals to slopes from a linear model and I can't figure out how to get at them. As a cut 'n' paste example: ################# # dummy dataset - regression data for 3 treatments, each treatment with different (normal) variance x <- rep(1:10, length=30) y <- 10 - (rep(c(0.2,0.5,0.8), each=10)*x)+c(rnorm(10, sd=0.1), rnorm(10,

I am currently using samba to try and replace a windows NT box as the default print server. All is working well except for one printer driver. All drivers were installed from a win2k machine onto the samba print$ share. The problem that I'm having is with a driver for the HP laser jet 4000N printer. The PCL driver works and loads quickly. The PCL 6 driver works, but the properties

Hello, We've got a dataset with several variables, one of which we're using to split the data into 3 smaller subsets. (as the variable takes 1 of 3 possible values). There are several more variables too, many of which we're using to fit regression models using lm. So I have 3 models fitted (one for each subset of course), each having slope estimates for the predictor variables.

Not really r-specific: Z = (b1 - b2) / SQRT ( SEb1^2 + SEb2^2) -------Original Message------- From: Gijsbert Stoet <stoet at volition.wustl.edu> Sent: 07/20/03 09:51 PM To: r-help at stat.math.ethz.ch Subject: [R] how to test whether two slopes are sign. different? > > Hi, suppose I do want to test whether the slopes (e.g. determined with lsfit) of two different population are

Hi everyone, Suppose I have a 3D array of datasets, where say dimension 1 corresponds to cases, dimension 2 to datasets, and dimension 3 to observations within a dataset. As an example, suppose I do the following: > x <- sample(1:20, 48, replace=TRUE) > datasets <- array(x, dim=c(4,3,2)) Here, for each j=1,2,3, I'd like to think of datasets[,j,] as a single data matrix with

Dear all, I am trying to estimate the prediction from a fixed effects model and their confidence intervals as well. Though I do not want to include in the prediction and at the confidence intervals the intercept. For that reason I used the argument incl.non.slopes=FALSE. But either if it is TRUE or FALSE it does not have any difference and also the system does not provide any warning. I really

I've also posted this message to the lprng list, but as I'm currently not sure where the problem lies, I'm posting it here too in the hope that someone has a clue..... I have recently installed a printer accounting system on my systems, and changed the print model for some of my users. In most cases, this has been fine, but users who are using HP Laserjet 4 printers are experiencing

On 01/22/2018 08:40 AM, Ulrich Bodenhofer wrote: > Thanks a lot, I?aki, this is a perfect solution! I already implemented > it and it works great. I'll wait for 2 more days before I submit the > revised package to CRAN - in order to give others to comment on it. It's very easy for 'pictures of code' (unevaluated code chunks in vignettes) to drift from the actual

Hi I have (8 measures * 96 groups) = 768 datasets for which I did linear regressions using lm(). Now I want to compare the slopes for each of the 8 measures in each of the 96 groups. As I understand , I can not use > anova(lm1, ..., lm8) as the lm1 ... lm8 are based on different datasets. I also read in previous discussions in this list, that I can see if the slope +- stddev(slope)