.edu]
> Sent: Thursday, February 12, 2015 9:27 PM
> To: PIKAL Petr
> Cc: r-help@r-project.org
> Subject: Re: [R] suggestion for optimal plotting to show significant
> differences
>
> ## The next step is to think of this in the analysis of covariance
> setting.
>
> ## this
, 3), more=TRUE)
print(AiB, split=c(2, 2, 2, 3), more=TRUE)
print(AiBj, split=c(2, 1, 2, 3), more=FALSE)
## dev.off()
On Thu, Feb 12, 2015 at 9:48 AM, PIKAL Petr wrote:
> Hi Rich
>
>> -Original Message-
>> From: Richard M. Heiberger [mailto:r...@temple.edu]
>> Se
Hi Rich
> -Original Message-
> From: Richard M. Heiberger [mailto:r...@temple.edu]
> Sent: Wednesday, February 11, 2015 10:53 PM
> To: PIKAL Petr
> Cc: r-help@r-project.org
> Subject: Re: [R] suggestion for optimal plotting to show significant
> differences
>
>
>> -Original Message-
>> From: Richard M. Heiberger [mailto:r...@temple.edu]
>> Sent: Friday, February 06, 2015 6:14 PM
>> To: PIKAL Petr
>> Cc: r-help@r-project.org
>> Subject: Re: [R] suggestion for optimal plotting to show significant
&g
t regards
Petr
> -Original Message-
> From: Richard M. Heiberger [mailto:r...@temple.edu]
> Sent: Friday, February 06, 2015 6:14 PM
> To: PIKAL Petr
> Cc: r-help@r-project.org
> Subject: Re: [R] suggestion for optimal plotting to show significant
> differences
>
>
I would try one of these illustrations for starts.
interaction2wt (two-way tables) is designed to be used with aov() for testing.
interaction2wt shows all main effects and all two-way interactions for
many factors.
test <-
structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L,
Dear all
I would like to ask for your opinion about possible graphical representation of
such data.
> dput(test)
structure(list(item = structure(c(1L, 1L, 1L, 1L, 1L, 1L, 1L,
1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 1L, 2L, 2L, 2L, 2L, 2L,
2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L, 2L), .Lab
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