similar to: Multiple regression intercept

Full_Name: Joerg Rauh Version: 2.5.0 OS: Windows 2000 Submission from: (NULL) (84.168.226.163) Following Michael J. Crawley "Statistical Computing" on page 9 the worms.txt is required. After downloading it from the book's supporting website, which is http://www.bio.ic.ac.uk/research/mjcraw/statcomp/data/ I visually check the data against the book and they look identical. Then I do

hi folks, in my (unlucky) first test of ogg vs other encoders, i found a case where wma and mp3pro sound much better than ogg at 64k. can anyone suggest a setting that i haven't tried yet that can rival the wma and mp3pro samples at 64k? it's the "gravel effect" that is troublesome. the part in question is the first 15 seconds of this wave file:

Hello, I have somewhat of a weird data set and am attempting to create a barplot with it. I have 8 columns with different variables and their percentages. I have 1 column with representations of 4 different treatments the variables undergo. I also have 1 column with year the data was recorded. I want to create a bar plot that plots all 8 variables grouped by treatment and year. I've tried

o <- (structure(list(sand.silt = structure(list(statistic = structure(185, .Names = "W"), parameter = NULL, p.value = 0.0478835773838087, null.value = structure(0, .Names = "location shift"), alternative = "two.sided", method = "Wilcoxon rank sum test with continuity correction", data.name = ".column by site"), .Names =

Hello everybody, I need an help because I don´t know if the command for the ANOVA analysis I am performing in R is correct. Indeed using the function aov I get the following error:"In aov (......) Error() model is singular" The structure of my table is the following: subject, stimulus, condition, sex, response Example: subject stimulus condition sex response

I would like to preform a t.test to each of the measured variables (sand.silt etc.) with a mean and sd for each of the treatments (up or down), and out put this as a table.... I am having a hard time starting- maybe it is to close to lunch. Any suggestions would be greatly appreciated. Stephen Sefick x <- (structure(list(sample. = structure(c(1L, 7L, 8L, 9L, 10L, 11L, 12L, 13L, 14L, 2L, 3L,

Dear R users, I face to a nested pattern and despite the numerous examples in the help I am still confused. I sampled bugs in different habitats within sites which were within rivers themselves within different regions. The habitat correspond to different substrata (not systematically present in all sites). For rivers and sites, I have environemental variables (e.g. altitude and slope of

Dear list members, I get the following error when using the glht function to perform a post hoc analysis for an ANOVA with repeated measures: require(nlme) lme_H2H_musicians = lme(H2H ~ Emotion*Material, data=musicians, random = ~1|Subject) require(multcomp) summary(glht(lme_H2H_musicians, linfct=mcp(Type = "Tukey")), test = adjusted(type = "bonferroni")) Error in

Hello everybody, problem solved, there was a typo. I wrote Type instead of Material Best ----Messaggio originale---- Da: angelo.arcadi@virgilio.it Data: 22-giu-2012 11.05 A: <r-help@r-project.org> Ogg: Error with glht function: Error in mcp2matrix(model, linfct = linfct) : Variable(s) 'Type' have been specified in 'linfct' but cannot be found in 'model'!

Dear R-list members, I need an help with the Multidimensional Scaling analysis (MDS). So far I used the cmdscale() command in R, but I did not get the perceptual map I would love to see, and I would like to know if it is possible to get it using R, and if yes how. I also had a look to the functions isoMDS() and sammoc() but with no luck. I summarize the experiment I performed, and I would ask you

Hi, I have a somewhat complicated relationship question. I''ve been banging my head about this for some time and have given in and decided to ask the list :) Here''s what I''m trying to achieve: Products can have variants. For example, a t-shirt could come in small, medium and large, but also black, green and blue in the first two sizes, but only blue in large.

I need to use Alt-F2 shortcut in Far Manager running with wineconsole. But Alt-F2 invokes standard Linux "run command" dialog. How can I intercept the Alt-F2 so that it is processed by Wine application?

I realize that the following has been talked about on this list many times before in some related way but I am going to ask for help anyway because I still don't know what to do. Suppose I have no intercept models such as the following : Y = B*X_1 + error Y = B*X_2 + error Y = B*X_3 + error Y = B*X_4 + error and I run regressions on each ( over the same sample of Y ) and now I want to

Hi all, Dear Dr. Wheeler, I am trying to use the lmPerm package to perform multiple regression on microarray data with certain empirical variables associated with treatments of the experiment. In order the circumvent the very conservative multiple test corrections such as Bonferroni and BH, I try to use permutated probabilities to assess associations. In addition to mu previous posting I

Hello, I'm implementing a function using non uniform B-Splines. Looking at the code of the bs() function, I realized that if the intercept was set to FALSE, the behavior of the function was the following (df is the number of degrees of freedom that I believe can be interpreted as the number of control points): - Compute df- ord + 1 _internal_ knots (ord is the order of the spline) - Add ord

Dear list, I'm trying to fit a glm model using family=poisson(link = "identity"). The problem is that the glm function fits a model with a negative intercept, which sounds like a nonsense to me, being the response a Poisson variable. >From a previous discussion on this list I've understood that the glm function uses IRLS for the fitting without any constraint so it is

It's easy to run a linear regression on a simple model without an intercept just by doing this: lm(y ~ x1 + x2 -1) Is there a similar trick to suppress the intercept when your model is in a large dataframe and you don't want to write out the names of individual columns? -- View this message in context:

I would appreciate if someone could tell me how to fit a non-intercept model using lrm (and not glm). The -1 in the formula of the glm does not work with lrm. Thanks, Clarissa [[alternative HTML version deleted]]

Dear R users, glm.fit() gave me the same AIC's regardless of TRUE or FALSE intercept option. > myX <- as.matrix(1:10) > myY <- 3+5*myX > foo <- glm.fit(x=myX, y=myY, family = gaussian(link = "identity"), intercept=TRUE) > foo$aic [1] 38.94657 > foo <- glm.fit(x=myX, y=myY, family = gaussian(link = "identity"), intercept=FALSE) > foo$aic [1]

Hi, dear R-help, I want to fit a Buckley-James censored regression without intercept. The function bj() inside the Design library have to have an intercept, I try Surv(y,d)~ 0 + x , or -1+x, or x-1, none works. Any suggestions? Is there another BJ() code out there that do not have to have an intercept? Or may be it is easier to modify the bj()? I need the estimator only, no need of var estimate