multiple treatments, one at a time, to same
pool
> >>> of patients. You are correct that interactions may be important in
this
> >>> problem. I am only trying to help him frame the problem using an
analogy.
> >>>
> >>>
> >>> ** **
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 i
the group effect only, as originally shown
>>>
>>> -- Bert
>>>
>>> On Mon, Oct 10, 2011 at 7:43 AM, Anupam wrote:
>>>
>>> Groups are different treatments given to Users for your Outcome
>>> (measurement) of interest. Take this
sers for your Outcome
>> (measurement) of interest. Take this idea forward and you will have an
>> answer.
>>
>> Anupam.
>> -Original Message-----
>> From: r-help-boun...@r-project.org [mailto:r-help-boun...@r-project.org]
>> On
>> Behalf Of Bert Gu
, October 10, 2011 7:36 PM
To: gj
Cc: r-help@r-project.org
Subject: Re: [R] help with statistics in R - how to measure the effect of
users in groups
Assuming your data are in a data frame, yourdat, as:
User Group Value
u1 1 !0
u2 2 5
u3 3 NA
...(etc)
where Group is
I should have added...
If your design is not "nearly" balanced, main effects and interactions will
not have any "natural" interpretation because they will be (partially)
confounded. (I realize "nearly" is not a very useful characterization, but I
do not know a better one, as it probably depends on
Assuming your data are in a data frame, yourdat, as:
User Group Value
u1 1 !0
u2 2 5
u3 3 NA
...(etc)
where Group is **explicitly coerced to be a factor,**
then you want the User x Group interaction, obtained from
lm( Value ~ Group*User,data = yourdat)
Ho
Hello,
In package "qualityTools" you can find one way to perform this analysis
through the gageRR() function.
The effect of an operator on the mesasurement system (Reproductibility) is
to me equivalent to the effect you try to study of your users when they are
in different groups.
Regards,
Carlos
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 wrote:
> >
> > Hi Petr,
> >
> > It's
>
> 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
> u110 5N/A
> u2 6 N/A 4
> u3
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
u110 5N/A
u2 6 N/A 4
u3 5 2
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
att
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