[R] Converting SAS Code

MacQueen, Don macqueen1 at llnl.gov
Fri Sep 29 22:43:52 CEST 2017

For the initial data step, assuming a data frame named stress already exists, and using base R, you can start with something like this:

barcodes.to.delete <- c('16187DD4015', '16187DD6002',   {complete the comma-delimited vector of barcodes you don't want}  )

yield <- subset(stress,  !(barcode %in% barcodes.to.delete) )
yield <- subset(yield , !(field %in% c('YY','HB') )

## the above three lines could be done in a single line, but it would be long, ugly, hard to read, and hard to validate.
## easier to split it into a few steps

## another way, still using base R, and with a different syntax for the subsetting
records.to.drop <- stress$barcode %in% barcodes.to.delete | stress$yield %in% c('YY', 'HB')
yield <- stress[ !records.to.drop , ]

I think these are examples of doing it "the R way", not thinking in terms of directly translating SAS code to R code.

I used to use SAS a lot, but I don't know what the line
  *Yield Champagin;

Don MacQueen
Lawrence Livermore National Laboratory
7000 East Ave., L-627
Livermore, CA 94550
Lab cell 925-724-7509

On 9/29/17, 5:47 AM, "R-help on behalf of Andrew Harmon" <r-help-bounces at r-project.org on behalf of andrewharmon42 at gmail.com> 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;
    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
    Andrew Harmon
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