[R] help with statistics in R - how to measure the effect of users in groups

[Petr PIKAL]

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.pikal at 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.pikal at 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 at 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 at 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.