search for: neter

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 source of variation SS df MS F gender 0.12 1 0.12 0.74 bon...

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

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 a fixed variance to work with, but I couldn't find a function where...

I'm wondering how to choose an appropriate linear model for a given problem. I have been reading Applied Linear Regression Models by John Neter, Michael H Kutner, William Wasserman and Christopher J. Nachtsheim. I'm still not clear how to choose an appropriate linear model. For multi-factor ANOVA, shall I start with all the interaction terms and do an F-test to see with interaction terms are not significant, then do a linear regressio...

...ual items. Edelman and coworkers made a linear regression of Y on X and now I would like to ascertain the importance of the fact that X was measured with error for the utility of the formula in clinical practice (since I believe it is being misused by ignoring this fact - and more). I found in Neter, Wasserman and Kutner 3. ed a general discussion of the problem - but would very much like a more recent presentation if available and application in R. Best wishes Troels Ring Aalborg, Denmark

...f Y_hat: sqrt(MSE(1/n + (x-x_bar)^2/SS_x)), not the standard errors of Y_new (predicted value): sqrt(MSE(1 + 1/n + (x-x_bar)^2/SS_x)). Is there a reason this quantity is called the "standard error of predicted means" if it doesn't relate to the prediction distribution? Turning to Neter et al.'s Applied Linear Statistical Models, I note that if we have multiple observations, then the standard error of the mean of the predicted value: sqrt(MSE(1/m + 1/n + (x-x_bar)^2/SS_x)), reverts to the standard error of the sampling distribution of Y-hat, as m, the number of samples, gets...

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) x<-c(21,34,23,26,26,29,22,29,30,28,18,16,19,25,29) xmean<-x-mean(x) grupo<-factor(rep(c(1,2,3),5)) datos<-data.frame(y,xmean,grupo) and I have done the following modelo<-lm(y~xmean+grupo,data=datos)...

...components along with approximate confidence intervals using the NLME package. However, I do not know how to specify the random option because of two problems. First, I do not know how to enter the interaction term into the option. Second, I do not know how to enter in the covariance matrix (see Neter et. al., Applied Linear Statistical Models, 4th ed., page 977). Is there anyone who has confronted this problem before that would be willing to help? Thank you. Philip Turk

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

...his issue, please? Kind regards Mehrshad 1. Norusis MJ. SPSS 16.0 guide to data analysis. Upper Saddle River: Prentice Hall Inc.; 2008. 2. Norusis MJ. SPSS 16.0 statistical procedures companion. Upper Saddle River: Prentice Hall Inc.; 2008. 3. Kutner M, Nachtsheim C, Neter J, Li W. Applied linear statistical models. 5th ed. New York: McGraw-Hill; 2005. [[alternative HTML version deleted]]

...his a bug? Or should I be using lme() or some other function when the number of factors is greater than the "limit"? I would also like to hear some views as to whether Error() should be used for repeated measures, pro & cons,etc? I have found differing views in books. For example, Neter et al "applied linear statistical models " uses simply the combined treatment by subject interaction mean square when testing main effects and their interactions. They do state that the relaxation of the assumptions of a repeated measures model can be made by the inclusion of first-o...

...with multiple predictors), you can easily calculate a pure error test for > lack of fit. The error term will be partitioned into pure error (error within replicates) > , and a lack of fit error and the F-test can be used to test if you have chosen an > adequate regression model. See Neter, Kutener, Nachtsheim, and Wasserman fourth edition > page 115, or Draper and Smith. Bill Venables wrote "...It makes it > impossible to write code to do it automatically, but if you know > what you are doing, the procedure is simple with the software you > have. As with so many...

...n the "limit"? >>>>> >>>>> I would also like to hear some views as to whether Error() should be >>>>> used for repeated measures, pro & cons,etc? I have found differing >>>>> views >>>>> in books. For example, Neter et al "applied linear statistical >>>>> models " >>>>> uses simply the combined treatment by subject interaction mean square >>>>> when testing main effects and their interactions. They do state >>>>> that the >>>>...

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

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 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

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