similar to: ggplot and boxplots

It looks like your V3 is a factor. testing_ggplot <- data.frame( V1=factor(c(256, 256, 256, 272, 272, 272)), V2=c("Disabled", "Disabled", "Enabled", "Disabled", "Enabled", "Enabled"), V3=681:686) library(ggplot2) ggplot(testing_ggplot, aes(V2, V3 )) + geom_boxplot() + facet_wrap( ~ V1) + labs(title="what you

Howdy, R Grues I have enjoyed R, but I cannot solve one problem easily. Please help my problem. When I tried the R script, I got the following Error. This error results from input data file exported through a Excel spreadsheet software. Error in step(lm(pop.rate ~ as.numeric(year) + as.factor(policy) + as.numeric(nation.grant) + ?: ??number of rows in use has changed: remove missing values?

Dear all, I'm using the latest version of the package lme4 and R version 2.7.2 (2008-08-25). After I run the model, I get the results of the model (cf. below). Then, I run an ANOVA using the "anova" function and I get the following message "Error in anova(lmer1) : Calculated PWRSS for a LMM is negative". I went trough the R-mailing list and a similar error message was

Hi, We are looking into replacing our current storage solution and are evaluating gluster for this purpose. Our current solution uses a SAN with two servers attached that serve samba and NFS 4. Clients connect to those servers using NFS or SMB. All users' home directories live on this server. I would like to have some insight in who else is using gluster for home directories for about 500

Hi Rik, Nice clarity and detail in the description. Thanks! inline... On Wed, Mar 7, 2018 at 8:29 PM, Rik Theys <Rik.Theys at esat.kuleuven.be> wrote: > Hi, > > We are looking into replacing our current storage solution and are > evaluating gluster for this purpose. Our current solution uses a SAN > with two servers attached that serve samba and NFS 4. Clients connect to

Hi, I have a question about estimating IRT models by using nlme, not just rasch model, but also other models. Behavior Research Methods <http://www.springerlink.com/content/1554-351x/> Volume 37, Number 2 <http://www.springerlink.com/content/1554-351x/37/2/>, 202-218, DOI: 10.3758/BF03192688 Using SAS PROC NLMIXED to fit item response theory models (2005). Ching-Fan