[R] Converting SAS Code

Fri Sep 29 20:45:49 CEST 2017

I wish to second this approach to learning R. 

I tried for several years to translate other stat programs  or provide 
parallel analyses with R. 
This dabbling-in-R approach did not work
. 
When a transferred to a research unit  that could ill afford commercial 
software, I devoted my entire time to doing everything in R. 
This was a difficult learning process, but I eventually became proficient 
in R. 

The conceptual paradigm for R is only marginally commensurate with that of 
standard statistical software. 
You must immerse yourself in R to become proficient. 

Good luck,
Joe

Bert Gunter <bgunter.4567 at gmail.com> 
Sent by: "R-help" <r-help-bounces at r-project.org>
09/29/2017 02:09 PM

To
"Kevin E. Thorpe" <kevin.thorpe at utoronto.ca>, 
cc
R-help <r-help at r-project.org>, Andrew Harmon <andrewharmon42 at gmail.com>
Subject
Re: [R] Converting SAS Code

I will offer an opinion, with which others may fairly take issue.

If you are coming from SAS and wish to learn R, you should forget about 
SAS
entirely; it is ancient and convoluted. But more to the point, as others
have already suggested, you will only confuse and hamstring yourself 
trying
to convert the programming paradigms of one language into another. Better
to consider the **tasks** you wish to accomplish and learn how to approach
them in the new language. I would add that this especially includes
learning about R's varied data structures for which there is no cognate in
SAS I think (correction requested if I'm wrong about this).

If this is a one-off, just finding a local resource to do the job for you
might be the best approach.

Cheers,
Bert

Bert Gunter

"The trouble with having an open mind is that people keep coming along and
sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )

On Fri, Sep 29, 2017 at 10:21 AM, Kevin E. Thorpe 
<kevin.thorpe at utoronto.ca>
wrote:

> Regarding point 3, as a moderator I have been helping Andrew get this 
post
> out to the list over the past week. His previous attempts were encoded 
in
> some way that the listserv rejected. He sent me the post via his gmail
> account and viewing the source I saw it had at least both plain test and
> HTML an I said it was worth a try to post it. Certainly on my mail 
client
> his post displays acceptably with the notice that the HTML alternative 
was
> removed.
>
> Kevin
>
> On 09/29/2017 09:51 AM, Michael Dewey wrote:
>
>> You might get better answers if you
>>
>> 1 - break this down into separate issues
>> 2 - tell us what you want to achieve in words rather than SAS, we all
>> read English but few of us speak SAS
>> 3 - post in plain text not HTML as HTML mangles your post
>>
>> On 29/09/2017 13:47, Andrew Harmon wrote:
>>
>>> Hello all,
>>>
>>> My statistical analysis training up until this point has been entirely
>>> done
>>> in SAS. The code I frequently used was:
>>>
>>> *Yield Champagin;
>>>
>>> data yield;
>>>
>>> set stress;
>>>
>>> if field='YV' then delete;
>>>
>>> if field='HB' then delete;
>>>
>>> if barcode='16187DD4015' then delete;
>>>
>>> if barcode='16187DD6002' then delete;
>>>
>>> if barcode='16187DD2007' then delete;
>>>
>>> if barcode='16187DD5016' then delete;
>>>
>>> if barcode='16187DD8007' then delete;
>>>
>>> if barcode='16187DD7010' then delete;
>>>
>>> if barcode='16187DD7007' then delete;
>>>
>>> if barcode='16187DD8005' then delete;
>>>
>>> if barcode='16187DD6004' then delete;
>>>
>>> if barcode='16187DD5008' then delete;
>>>
>>> if barcode='16187DD7012' then delete;
>>>
>>> if barcode='16187DD6010' then delete;
>>>
>>> run; quit;
>>>
>>>
>>>
>>> Title'2016 Asilomar Stress Relief champagin yield';
>>>
>>> proc mixed method=reml data=yield;
>>>
>>> class rep Management Foliar_Fungicide Chemical_Treatment;
>>>
>>> model Grain_Yield__Mg_h_ 
=Management|Foliar_Fungicide|Chemical_Treatment
>>> Final_Stand__Plants_A_ / outpred=resids residual ddfm=kr;
>>>
>>> random rep rep*Management rep*Management*Foliar_Fungicide;
>>>
>>> lsmeans Management|Foliar_Fungicide|Chemical_Treatment / pdiff;
>>>
>>> ods output diffs=ppp lsmeans=means;
>>>
>>> ods listing exclude diffs lsmeans;
>>>
>>> run; quit;
>>>
>>> %include'C:\Users\harmon12\Desktop\pdmix800.sas';
>>>
>>> %pdmix800(ppp,means,alpha=0.10,sort=yes);
>>>
>>> ods graphics off;
>>>
>>> run; quit;
>>>
>>> proc univariate data=resids normal plot; id Barcode Grain_Yield__Mg_h_
>>> pearsonresid; var resid;
>>> proc print data=resids (obs=3);run;
>>>
>>> Can someone please help me convert my code to R? Any help would be 
much
>>> appreciated.
>>>
>>>
>>> Thanks,
>>>
>>>
>>> Andrew Harmon
>>>
>>>     [[alternative HTML version deleted]]
>>>
>>> ______________________________________________
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>>> PLEASE do read the posting guide http://www.R-project.org/posti
>>> ng-guide.html
>>> and provide commented, minimal, self-contained, reproducible code.
>>>
>>> ---
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>>>
>>>
>>>
>>
> --
> Kevin E. Thorpe
> Head of Biostatistics,  Applied Health Research Centre (AHRC)
> Li Ka Shing Knowledge Institute of St. Michael's Hospital
> Assistant Professor, Dalla Lana School of Public Health
> University of Toronto
> email: kevin.thorpe at utoronto.ca  Tel: 416.864.5776  Fax: 416.864.3016
>
> ______________________________________________
> R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
> https://stat.ethz.ch/mailman/listinfo/r-help
> PLEASE do read the posting guide http://www.R-project.org/posti
> ng-guide.html
> and provide commented, minimal, self-contained, reproducible code.

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______________________________________________
R-help at r-project.org mailing list -- To UNSUBSCRIBE and more, see
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.

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