similar to: Bounded memory ANOVA

Hello, I'm trying to use R statistical packages to do ANOVA analysis using aov() and lm(). I'm having a problem when I have a large data set for input data from Full Factorial Design Experiment with replications. R seems to store everything in the memory and it fails when memory is not enough to hold the massive computation. Have anyone successfully used R to do such analysis before? Are

Hi, I am running a simulation and have to perform ANOVA to determine the rank of factors. Used the aov() function and it works great for full factorial design. 1. For a massive set of data, I tried using biglm, while it can create the linear model, all the residuals (for assumption validation) are not recorded and the sum of squares are not there, just the estimated regression coefficient, 95%

I guess my subject says it all. But I loaded a dataset in spss and used the foreign package to read and save it in R. Running an anova (using the aov command) gives a different F and p value in R than it does in SPSS. ANy idea what is going on? -- View this message in context: http://n4.nabble.com/R-ANOVA-gives-diferent-results-than-SPSS-tp1477322p1477322.html Sent from the R help mailing list

Hello colleagues, I have tried to use the package biglm. I want to specify a multivariate regression with a weight. I have imported a large dataset with the library(bigmemory). I load the library (biglm) and specified a regression with a weight. But I get everytime a error message like ?object not found? or ?`weights' must be a formula? or "error in eval(expr, envir, enclos)". I

If a package defined an S3 generic and an S4 generic for the same function (so as to add methods for S4 classes to the existing code), how do I set up the namespace to have them exported? With import(stats) exportMethods(bigglm) importClassesFrom(DBI) useDynLib(biglm) export(biglm) export(bigglm) in NAMESPACE, the S3 generic is not exported. > methods("bigglm") [1] bigglm.RODBC*

I've been working with a rather large data set (~10M rows), and while biglm works beautifully for generating coefficients, it does not report an r-squared. It does report RSS. Any idea on how one could coax an R-squared out of biglm? Thanks in advance for any help with this! Bryan Lim Lecturer Department of Finance University of Melbourne [[alternative HTML version deleted]]

Hi R experts, I used biglm to construct a model (which has categorical variables). When I run predict on the model output on a new data (for testing) or on the same data, I get only NA's. I'm able to run predict with some other models constructed with biglm. One reason I suspect is that the model itself has a few undefined terms (NA's). I'm wondering if there's any way to

Full_Name: Tanya Logvinenko Version: 1.7.0 OS: Windows 2000 Submission from: (NULL) (132.183.156.125) For unbalanced design, I ran into problem with ANOVA (aov function). The sum of squares for only for the second factor and total are computed correctly, but sum of squares for the first factor is computed incorreclty. Changing order of factors in the formula changes the ANOVA table. For the

Hi Sir, Thanks for making package available to us. I am facing few problems if you can give some hints: Problem-1: The model summary and residual deviance matched (in the mail below) but I didn't understand why AIC is still different. > AIC(m1) [1] 532965 > AIC(m1big_longer) [1] 101442.9 Problem-2: chunksize argument is there in bigglm but not in biglm, consequently,

Dear all, I'm trying to access the Sums of Squares resulting from a summary(aov(....)) so I can use them in a function. Is there an easy way to access these? The structure of a summary.aov object is something like this: > str(summary(fhc.aov)) List of 5 $ Error: PPNR :List of 1 ..$ :Classes anova and `data.frame': 1 obs. of 5 variables: .. ..$ Df : num 70 .. ..$

Dear all, I have problems to code contrasts for performing an asymmetrical anova with aov(). I am using aov() because I want to get the Mean Squares for further analyses. I didn't find any solution to my problem in the help files of functions aov(), contrasts(), C(), etc. Let's say I have three locations, one with treatment P, and two with treatment C: >

Hi everyone, I am fairly new to R, and I am aware that others have had this problem before, but I have failed to solve the problem from previous replies I found in the archives. As this is such a standard procedure in psychological science, there must be an elegant solution to this...I think. I would much appreciate a solution that even I could understand... ;-) Now, I want to calculate a

Hi, I'm doing anova on a matrix of multivariate data where I want to assess the effect of each column (element). My matrix is 86 rows x 31 columns. I've created a grouping factor of length 86 containing group assignments of 6 types. Then I run: x<- aov(matrix~grouping.factor) summary(aov.fit.raw, test="Wilks") This is working fine enough, but I'm getting different

Hi, I am using the: pcf.aov<-aov(meas~op+part, data=pcf.ex2), command to perform a two way ANOVA. When I save the: sumpcf<- summary.aov(pcf.aov), result of the summary.aov command in a variable I need to access the individual pieces of information in the summary. The summary appears to be a list and I am having a hard time finding a way to get at the information in the summary.

Dear useRs, I've just encountered a serious problem involving the F-test being carried out in aov() and anova(). In the provided example, aov() is not making the correct F-test for an hypothesis involving the expected mean square (EMS) of a factor divided by the EMS of another factor (i.e., instead of the error EMS). Here is the example: Expected Mean Square

Hi I am attempting Anova analysis to compare results from four groups (Samp1-4) which are lists of intensities from the experiment. I am doing this by first creating a structured list of the data and then conducting the ANOVA (Script provided below). Im an R beginner so am not sure if I am using this correctly. Two major questions I have are: 1) Is using the code (zzz.aov <- aov(Intensity ~

I am executing a Repeated Measures Analysis of Variance with 1 DV (LOCOMOTOR RESPONSE), 2 Within-Subjects Factors (AGE, ACOUSTIC CONDITION), and 1 Between-Subjects Factor (SEX). Does anyone know whether the between-subjects factor (SEX) belongs in the Error Term of the aov or not? And if it does belong, where in the Error Term does it go? The 3 possible scenarios are listed below: e.g., 1.

Hi Folks, I have repeated measures for data on association time (under 2 acoustic condtions) in male and female frogs as they grow to adulthood (6 timepoints). Thus, two within-subject variables (Acoustic Condition: 2 levels, Timepoint: 6 levels) and one between-subject variable (Sex:male or female). I am pretty sure my distributions depart from normality but I would first like to simply run a

Hi, I have used the instruction aov in the following manner: res <- aov(qwe ~ asd) when I typed "res" I get: _________ Call: aov(formula = qwe ~ asd) Terms: asd Residuals Sum of Squares 0.0708704 0.5255957 Deg. of Freedom 1 8 Residual standard error: 0.2563191 Estimated effects may be unbalanced _________ I need to access the value of

Dear all, I am studying a dataset using the aov() function. The independant variable 'cds' is a factor() with 8 levels and here is the result in studying the dependant variable 'rta' with aov() : > summary(aov(rta ~ cds)) Df Sum Sq Mean Sq F value Pr(>F) cds 7 0.34713 0.04959 2.3807 0.02777 Residuals 92 1.91635 0.02083 The dependant variable