similar to: How to choose appropriate linear model? (ANOVA)

Hi, I want to use Maximum likelihood to estimate the parameters from my regression line. I have purchased the book "Applied linear statistical models" from Neter, Kutner, nachtsheim & Wasserman, and in one of the first chapters, they use maximum likelihood to estimate the parameters. Now I want to tried it for my self, but couldn't find the right function. In the book, they give

Dear friends, I found the thread on this subject this summer but wonder whether it has been taken any further. I have an important medical problem where X is computed from a three independent and complicated measurements (exchangeable sodium and potassium and total body water - i.e. X = (Nae+Ke)/TBW ) and Y is serum sodium concentration (all data in Edelman, JCI 1958). I have the individual

If I'm not mistaken, partial R-squared is the R^2 of the quantities plotted in a partial residual plot, so you can base the computation on that. Prof. Fox's `car' package on CRAN has a function for creating those plots, but you need to figure out the way to extract the quantities being plotted. [In any case, the basic tools for doing such computations are all in R, and it

Dear Sir/Madam Hi. I am a general paediatrician, and I have read *some* chapters of the following books(1-3). I think SPSS lacks some features that may be important in data analysis (for example: interval of correlation coefficient in bivariate normal distribution, PRESS, and MSPR in cross-validation). I am thinking about changing SPSS to R: 1. SPSS is very expensive for me to update.

Hello everyone I appologize for my lack of experience in statistical methods. I am an R user begginer and I am running a logit model using "zelig" and "pcse" packages. I will go to the point and is that Im having problems with interpreting the results of my models.. It is really simple (I guess for the most advanced scholars) however I really dont understand how to interpret

> From: "Alan T. Arnholt" <arnholt at math.appstate.edu> > To: Bill Venables <William.Venables at cmis.CSIRO.AU> > Cc: r-help at stat.math.ethz.ch, arnholt at math.appstate.edu > Subject: Re: [R] Lack of Fit test > Date: Wed, 23 Feb 2000 09:40:21 -0500 (EST) > X-Authentication: none > > > I guess my question was not adequately stated when I sent

Hi, I am trying a two way anova with unequal sample sizes but results are not as expected: I take the example from Applied Linear Statistical Models (Neter et al. pp889-897, 1996) growth rate gender bone development 1.4 1 1 2.4 1 1 2.2 1 1 2.4 1 2 2.1 2 1 1.7 2 1 2.5 2 2 1.8 2 2 2 2 2 0.7 3 1 1.1 3 1 0.5 3 2 0.9 3 2 1.3 3 2 expected results are

Hello, I'm looking for a textbook that can explain some of the math behind the intro-to-intermediate stuff like ANOVA, multiple regression, non- parametric tests, etc. A little background: I took an intro stats course last year and would like to further my education. Being as that was the highest (and only) stats class the local community college offers, it looks like I'm on

I hope this question is sufficiently different from the other requests for book recommendations that it's not repetitious. If not, I apologize in advance. I'm curious what standard reference books working statisticians, or biostatisticians, have within easy reach of their desk. I'm a computer systems administrator, and have a two-foot bookshelf directory under my monitor that contains

I've been trying to download from CRAN the floppy versions of the R source files: R-release-1.tar.gz, R-release-2.tar.gz I tried the servers in Seattle, Madison, and the Vienna Technical University. In each case, the file(s) were unavailable. Anne ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Anne E. York National Marine Mammal Laboratory Seattle WA 98115-0070 USA e-mail: anne.york at noaa.gov

I am still a little unclear in the difference between randomized block design and two-way factorial design after consulting a few books, including John Rice Mathematical Statistics and Data Analysis. Both put observations in cells corresponding to two factors of many levels. Both use the same computer program to analyze data. It seems that randomized block design can have only one observation

Simple question. For a simple linear regression, I obtained the "standard error of predicted means", for both a confidence and prediction interval: x<-1:15 y<-x + rnorm(n=15) model<-lm(y~x) predict.lm(model,newdata=data.frame(x=c(10,20)),se.fit=T,interval="confidence")$se.fit 1 2 0.2708064 0.7254615

Dear R users, I am trying to fit the following ANCOVA model in R2.4.0 Y_ij=mu+alpha_i+beta*(X_ij-X..)+epsilon_ij Particularly I am interested in obtaining estimates for mu, and the effects alpha_i I have this data (from the book Applied Linear Statistical Models by Neter et al (1996), page 1020) y<-c(38,43,24,39,38,32,36,38,31,45,27,21,33,34,28)

Hello dear R members. I have been learning the Anova syntax in order to perform an SS type III Anova with repeated measures designs (thank you Prof. John Fox!) And another question came up: where/what are the (between/within) residuals for my model? ############ Play code: phase <- factor(rep(c("pretest", "posttest", "followup"), c(5, 5, 5)),

(Have searched for this already) Hi, How do you find the strength of correlation between two variables using an ANOVA table? "Pr(>F)" gives the statistical significance of the association, but not the strength of the correlation. See data (from R) below Readable: "Df" "Sum Sq" "Mean Sq" "F value"

Hello everyone, I am doing an analysis on some data for a project, and do not have much background in either R or statistics, but have been pointed in the direction of doing ANOVA and then multiple comparisons on the data to give me the information I need. I was wondering if some of you could help me out. What I want to do is to do ANOVA on a data set like the following: ID G1 G2 G3 NG1 NG2

Hello Prof. Harrell and dear R-help mailing list, I wish to perform a non-parametric repeated measures anova. If what I read online is true, this could be achieved using a mixed Ordinal Regression model (a.k.a: Proportional Odds Model). I found two packages that seems relevant, but couldn't find any vignette on the subject: http://cran.r-project.org/web/packages/repolr/

Simple example: # Classification Tree with rpart library(rpart) # grow tree fit <- rpart(Kyphosis ~ Age + Number + Start, method="class", data=kyphosis) Now I would like to know how can I measure the "importance" of each of my three explanatory variables (Age, Number, Start) in the model? If this was a regression model, I could have looked at p values from the

I am conducting an experiment where students are put into 5 total groups (one is the control group). They are given a task and then I'm measuring if there are differences (A 5 X 1 between-subject design will be used for the experiment). I'm a little confused on the data explanation (or should I say how do I explain what is being analyzed versus just comparing values) Any help?

I have the attached data set (csv) and I want to run an analysis of variance on the wingsize data (comparing infected vs non-infected) within and between experiments. Can anyone help me with the command I should use? Many thanks Georgina PhD Student Division of Infection and Immunity B5-29, GBRC 120 University Place Glasgow G12 8TA Tel: 0141 330 5650