search for: nachtsheim

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 can estimate the...

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 regression on a model without the non-significant iteration term? Could som...

...s 10 coefficients. This means that we could only estimate models containing subsets of the coefficients. I therefore plan to compare alternative designs primarily in terms of their "estimation capacity" = percent of models of certain types that are actually estimable, following Li and Nachtsheim (2000) ?Model Robust Factorial Designs?, Technometrics, pp. 345-352. I propose to start with a half-fraction of a 12-run Plackett-Burman in 6 runs and a 2^3 in 8 runs, then move selected points to a middle value to obtain 3-level designs to compare in terms of estimation capacity. After I get t...

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

...favour about this 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]]

...redictors), 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 things in statistics,...

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

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