Hi I would try either some tree method (mvpart) or you can expand lm model also with users.
fit<-lm(value~variable+users, data=test.m) Anyway I am not an ultimate expert in statistics. so you shall also consult some appropriate literature which can be found in CRAN web. Did you try to look into the book I recommended? Petr > Thanks Petr. I will try it on the real data. > > But that will only show that the groups are different or not. > Is there any way I can test if the users are different when they are in > different groups? > > Regards > Gawesh > > On Mon, Oct 10, 2011 at 11:17 AM, Petr PIKAL <petr.pi...@precheza.cz> wrote: > > > > Hi Petr, > > > > It's not an equation. It's my mistake; the * are meant to be field > > separators for the example data. I should have just use blank spaces as > > follows: > > > > users Group1 Group2 Group3 > > u1 10 5 N/A > > u2 6 N/A 4 > > u3 5 2 3 > > > > > > Regards > > Gawesh > OK. You shall transform your data to long format to use lm > > test <- read.table("clipboard", header=T, na.strings="N/A") > test.m<-melt(test) > Using users as id variables > fit<-lm(value~variable, data=test.m) > summary(fit) > > Call: > lm(formula = value ~ variable, data = test.m) > > Residuals: > 1 2 3 4 6 8 9 > 3.0 -1.0 -2.0 1.5 -1.5 0.5 -0.5 > > Coefficients: > Estimate Std. Error t value Pr(>|t|) > (Intercept) 7.000 1.258 5.563 0.00511 ** > variableGroup2 -3.500 1.990 -1.759 0.15336 > variableGroup3 -3.500 1.990 -1.759 0.15336 > --- > Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 > > Residual standard error: 2.179 on 4 degrees of freedom > (2 observations deleted due to missingness) > Multiple R-squared: 0.525, Adjusted R-squared: 0.2875 > F-statistic: 2.211 on 2 and 4 DF, p-value: 0.2256 > > No difference among groups, but I am not sure if this is the correct way > to evaluate. > > library(ggplot2) > p<-ggplot(test.m, aes(x=variable, y=value, colour=users)) > p+geom_point() > > There is some sign that user3 has lowest value in each group. However for > including users to fit there is not enough data. > > Regards > Petr > > > > > > > > On Mon, Oct 10, 2011 at 9:32 AM, Petr PIKAL <petr.pi...@precheza.cz> > wrote: > > > > > Hi > > > > > > I do not understand much about your equations. I think you shall look > to > > > Practical Regression and Anova Using R from J.Faraway. > > > > > > Having data frame DF with columns - users, groups, results you could > do > > > > > > fit <- lm(results~groups, data = DF) > > > > > > Regards > > > Petr > > > > > > > > > > > > > > > > > > > > Hi, > > > > > > > > I'm a newbie to R. My knowledge of statistics is mostly self-taught. > My > > > > problem is how to measure the effect of users in groups. I can > calculate > > > a > > > > particular attribute for a user in a group. But my hypothesis is > that > > > the > > > > user's attribute is not independent of each other and that the > user's > > > > attribute depends on the group ie that user's behaviour change based > on > > > the > > > > group. > > > > > > > > Let me give an example: > > > > > > > > users*Group 1*Group 2*Group 3 > > > > u1*10*5*n/a > > > > u2*6*n/a*4 > > > > u3*5*2*3 > > > > > > > > For example, I want to be able to prove that u1 behaviour is > different > > > in > > > > group 1 than other groups and the particular thing about Group 1 is > that > > > > users in Group 1 tend to have a higher value of the attribute under > > > > measurement. > > > > > > > > > > > > Hence, can use R to test my hypothesis. I'm willing to learn; so if > this > > > is > > > > very simple, just point me in the direction of any online resources > > > about > > > > it. At the moment, I don't even how to define these class of > problems? > > > That > > > > will be a start. > > > > > > > > Regards > > > > Gawesh > > > > > > > > [[alternative HTML version deleted]] > > > > > > > > ______________________________________________ > > > > R-help@r-project.org mailing list > > > > https://stat.ethz.ch/mailman/listinfo/r-help > > > > PLEASE do read the posting guide > > > http://www.R-project.org/posting-guide.html > > > > and provide commented, minimal, self-contained, reproducible code. > > > > > > > > > > [[alternative HTML version deleted]] > > > > ______________________________________________ > > R-help@r-project.org mailing list > > https://stat.ethz.ch/mailman/listinfo/r-help > > PLEASE do read the posting guide > http://www.R-project.org/posting-guide.html > > and provide commented, minimal, self-contained, reproducible code. ______________________________________________ R-help@r-project.org mailing list https://stat.ethz.ch/mailman/listinfo/r-help PLEASE do read the posting guide http://www.R-project.org/posting-guide.html and provide commented, minimal, self-contained, reproducible code.