similar to: Help on Full Factorial Design

Dear all, I am working on a function formula.design that should automatically generate reasonable lm formulae for a number of different designs. All works well as long as all variables used are columns of the design data frame. For one function, I would like to incorporate a dummy variable for center points that is not a column of the design. Without this function, it would work like this (at

Hi R HELP, I consider the 2^3 factorial experiment described at page 177 of the book Statistics for Experimenters: Design, Innovation, and Discovery by George E. P. Box, J. Stuart Hunter, William G. Hunter (BHH2). This example use the following data in file BHH2-Data/tab0502.dat at ftp://ftp.wiley.com/ in /sci_tech_med/statistics_experimenters/BHH2-Data.zip run T C K y 1 1 -1 -1 -1 60 2

Dear all, I just noticed that the 0.9 update for FrF2 did not work out for Mac OS due to an error in an example that ran without error on all other platforms. I do not find any reason for this. In the past, umlauts or tab characters have sometimes been an issue, but I didn't find any of these. The function definition is FrF2(nruns = NULL, nfactors = NULL, factor.names = if

Dear developeRs, I encounter the following problem: in the current version of my package FrF2, certain calls to a functioni do not work when package combinat is loaded, because function combn from combinat masks the function from utils that my package uses. I tried to solve this issue by importing function combn into the namespace of FrF2; I don't need to export it, I just want to use it

Hi, I am new to bioconductor, trying to install KEGGSOAP package, but got warnings() when installing and error message when trying to load the package, can anyone suggest what went wrong? many thanks John > source("http://bioconductor.org/biocLite.R") Bioconductor version 2.11 (BiocInstaller 1.8.3), ?biocLite for help > biocLite("KEGGSOAP") BioC_mirror:

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

L.S. We would like to generate fractional design for a conjoint analysis. For example we would like to reduce 2x2x2x2x3 --> 12-16 profiles. We tried the R-package "conjoint" and we found an article which describes how to make fractional design for these kinds of studies with Algdesign: http://tolstoy.newcastle.edu.au/R/e10/help/att-8876/DCE_with_R.pdf However, the generated

Hi, I'm trying to use commands in FrF2 and once I install FrF2 and use the console command of library(FrF2) it loads required packages and ends with: Loading Tcl/Tk interface ... > then when I enter another command (only got to DATA<-read.table without an enter or more text) I get a non-responsive R console window with this along the bottom of the console window executing:

Hi, i need to create a fractional factorial design sufficient to estimate the main effects. The factors may have any number of levels, let's say any number from 2 to 6. I've tried to use the library conf.design , but i cannot figure out how to write the code. For example, what is the code for a design with 5 factors (2x3x3x5x2) and only main effects not confounded? thanks in advance!

Dear R Gurus: How do you put together a 2^2 (or even 2^k) factorial problem, please? Since you have 2 levels for A and B, do you put in "A+" and "A-" as factors, please? Thanks, Edna Bell

Hi, I'd like to apply a 2^k factorial design with k=10 parameters. Obviously this results in a quite long term for the model equation due to the high number of combinations of parameters. How can I specify the equation for the linear model (lm) without writing all combinations explicitly down by hand? Does a R command exist for this problematic? Thanks for your help in advance, Sven

Hello, I am planning a study with the main point to evaluate the interaction of two treatments, but for ethical reasons one cell is empty, that with patients receaving no treatment at all Treatment B

> On Mar 5, 2018, at 8:52 AM, Ding, Yuan Chun <ycding at coh.org> wrote: > > Hi Bert, > > I am very sorry to bother you again. > > For the following question, as you suggested, I posted it in both Biostars website and stackexchange website, so far no reply. > > I really hope that you can do me a great favor to share your points about how to explain the

Hi all, Does anybody know if it is possible to build a fractional factorial design in R? That is, suppose that we want do design an experiment with 3 factors with 2, 3 and 3 levels, respectivly. However we want to consider, let's say, only 6 from all possible level combinations. Does R design such experiment? Thanks in advance, Caio [[alternative HTML version deleted]]

Hello all, I´m trying to study a factorial design, but I can´t understand why did Df, Sum Sq and Mean Sq of residuals alter when I Split the interaction? I think that Split the interaction must not alter the residuals. Am I doing something wrong? Could anyone help me? My data and functions I tried are: Y<-c(196,213,183, 192,253,199, 251,331,276,

Dear R Gurus: I vaguely remember reading that if interaction was present in a factorial design, then the main effect results were suspect. However, I was reading a text which now uses the tests for main effects even if interaction is present. Which is correct, please? Thanks, Edna Bell

Hello! I have read somewhere (somehow, I can't seem to find it again, it's been a couple of months) that when analyzing factorial block design, the position where you put the block factor is important, even more when there are missing values. I understand that when using anova.lm, the order is sequential, so that if I want to check for a treatment effect, I should put my blocking factor

Hi Bert, I am very sorry to bother you again. For the following question, as you suggested, I posted it in both Biostars website and stackexchange website, so far no reply. I really hope that you can do me a great favor to share your points about how to explain the coefficients for drug A and drug B if run anova model (response variable = drug A + drug B). is it different from running three

This list provides help on R programming (see the posting guide linked below for details on what is/is not considered on topic), and generally avoids discussion of purely statistical issues, which is what your query appears to be. The simple answer is yes, you can fit the model as described, but you clearly need the off topic discussion as to what it does or does not mean. For that, you might try

Dear R users, I need to analyze data generated from a partial two-by-two factorial design: two levels for drug A (yes, no), two levels for drug B (yes, no); however, data points are available only for three groups, no drugA/no drugB, yes drugA/no drugB, yes drugA/yes drug B, omitting the fourth group of no drugA/yes drugB. I think we can not investigate interaction between drug A and drug B,