[R] SpreadLevelPlot for more than one factor

[Ashim Kapoor]

Dear Sir,

Many thanks and Best Regards,
Ashim.

On Sun, Jan 14, 2018 at 9:05 PM, Fox, John <jfox at mcmaster.ca> wrote:

> Dear Ashim,
>
> I’ll address your questions briefly but they’re really not appropriate for
> this list, which is for questions about using R, not general statistical
> questions.
>
> (1) The relevant distribution is within cells of the wool x tension
> cross-classification because it’s the deviations from the cell means that
> are supposed to be normally distributed with equal variance. In the
> warpbreaks data there are only 9 cases per cell. If you examine all of
> these deviations simultaneously, that’s equivalent to examining the
> residuals from the two-way ANOVA model fit to the data.
>
> (2) Yes, (d) and (e) visualize simple effects, and (a) and (b) visualize
> main effects, the latter only because the data are balanced.
>
> Best,
>  John
>
> -------------------------------------
> John Fox, Professor Emeritus
> McMaster University
> Hamilton, Ontario, Canada
> Web: http://socserv.mcmaster.ca/jfox/
>
>
>
>
> On 2018-01-09, 10:18 AM, "Ashim Kapoor" <ashimkapoor at gmail.com> wrote:
>
> >Dear Sir,
> >
> >
> >Many thanks for your reply.
> >
> >
> >I have a query.
> >
> >
> >
> >I have a whole set of distributions which should be made normal /
> >homoscedastic. Take for instance the warpbreaks data set.
> >
> >
> >
> >We have the following boxplots for the warpbreaks dataset:
> >
> >
> >a. boxplot(breaks ~ wool)
> >
> >b. boxplot(breaks ~ tension)
> >
> >c. boxplot(breaks ~ interaction(wool,tension))
> >d. boxplot(breaks ~ wool @ each level of tension)
> >e. boxplot(breaks ~ tension @ each level of wool)
> >
> >
> >Now should we not be making a-e normal and homoscedastic? Should we not
> >make a giant collection of boxplots from a-e and use the SpreadLevelPlot
> >on this entire collection?
> >
> >
> >A second query : (d) and (e) are the distribution of the simple effects
> >of factor wool and tension @ each level of the other. Is that correct?
> >Are (a) and (b) the distribution of the main effect of wool and tension?
> >Please confirm.
> >
> >
> >
> >Best Regards,
> >Ashim
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >On Sun, Jan 7, 2018 at 8:05 PM, Fox, John
> ><jfox at mcmaster.ca> wrote:
> >
> >Dear Ashim,
> >
> >Try spreadLevelPlot(breaks ~ interaction(tension, wool), data=warpbreaks)
> >.
> >
> >I hope this helps,
> > John
> >
> >-----------------------------
> >John Fox, Professor Emeritus
> >McMaster University
> >Hamilton, Ontario, Canada
> >Web:
> >socialsciences.mcmaster.ca/jfox/ <http://socialsciences.mcmaster.ca/jfox/
> >
> >
> >
> >
> >> -----Original Message-----
> >> From: R-help [mailto:r-help-bounces at r-project.org] On Behalf Of Ashim
> >> Kapoor
> >> Sent: Sunday, January 7, 2018 12:08 AM
> >> To: r-help at r-project.org
> >> Subject: [R] SpreadLevelPlot for more than one factor
> >>
> >> Dear All,
> >>
> >> I want a transformation which will make the spread of the response at
> >>all
> >> combinations of  2 factors the same.
> >>
> >> See for example :
> >>
> >> boxplot(breaks ~ tension * wool, warpbreaks)
> >>
> >> The closest I  can do is :
> >>
> >> spreadLevelPlot(breaks ~tension , warpbreaks) spreadLevelPlot(breaks ~
> >>wool ,
> >> warpbreaks)
> >>
> >> I want to do :
> >>
> >> spreadLevelPlot(breaks ~tension * wool, warpbreaks)
> >>
> >> But I get :
> >>
> >> > spreadLevelPlot(breaks ~tension * wool , warpbreaks)
> >> Error in spreadLevelPlot.formula(breaks ~ tension * wool, warpbreaks) :
> >>   right-hand side of model has more than one variable
> >>
> >> What is the corresponding appropriate function for 2 factors ?
> >>
> >> Many thanks,
> >> Ashim
> >>
> >>       [[alternative HTML version deleted]]
> >>
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> >
> >
> >
> >
> >
>
>

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