If it is only for the Scoring step, OP does not need to replicate the original data X times use: PROC SCORE , the REPLICATE variable in SCORE= dataset will to do this job, for example:

data Remission; input remiss cell smear infil li blast temp; label remiss='Complete Remission'; datalines; 1 .8 .83 .66 1.9 1.1 .996 1 .9 .36 .32 1.4 .74 .992 0 .8 .88 .7 .8 .176 .982 0 1 .87 .87 .7 1.053 .986 1 .9 .75 .68 1.3 .519 .98 0 1 .65 .65 .6 .519 .982 1 .95 .97 .92 1 1.23 .992 0 .95 .87 .83 1.9 1.354 1.02 0 1 .45 .45 .8 .322 .999 0 .95 .36 .34 .5 0 1.038 0 .85 .39 .33 .7 .279 .988 0 .7 .76 .53 1.2 .146 .982 0 .8 .46 .37 .4 .38 1.006 0 .2 .39 .08 .8 .114 .99 0 1 .9 .9 1.1 1.037 .99 1 1 .84 .84 1.9 2.064 1.02 0 .65 .42 .27 .5 .114 1.014 0 1 .75 .75 1 1.322 1.004 0 .5 .44 .22 .6 .114 .99 1 1 .63 .63 1.1 1.072 .986 0 1 .33 .33 .4 .176 1.01 0 .9 .93 .84 .6 1.591 1.02 1 1 .58 .58 1 .531 1.002 0 .95 .32 .3 1.6 .886 .988 1 1 .6 .6 1.7 .964 .99 1 1 .69 .69 .9 .398 .986 0 1 .73 .73 .7 .398 .986 ; run;

proc sort data=Remission; by Remiss; run; ods select none; proc surveyselect data=Remission out=samp rate=1 method=urs outhits rep=10; strata remiss; run; ods select all;

proc sort data=samp;by Replicate; run;

proc logistic data=samp outest=est noprint; by Replicate; model remiss(event='1')=cell smear infil li blast temp; run;

proc score data=Remission(rename=(remiss=remiss0)) out=out score=est type=parms; by replicate; var cell smear infil li blast temp; run;

On Tue, 22 Sep 2009 10:43:29 -0500, Data _null_; <iebupdte@GMAIL.COM> wrote:

>No read it again > >> this means that I need to have to create a dataset with my original >> data repeated X times, each time with a new value of REPLICATE > > >On 9/22/09, oloolo <dynamicpanel@yahoo.com> wrote: >> add one more option: OUTHITS >> otherwise multiple replicated records will be collapsed into one >> besides, for Bootstrap analysis, OP needs to sample WITH REPLACEMENT, not >> WITHOUT REPLACEMENT >> >> **********************; >> ods select none; >> proc surveyselect data=sashelp.class out=class100 >> rate=1 method=urs rep=100 outhits; >> run; >> ods select all; >> **********************; >> >> >> On Tue, 22 Sep 2009 10:23:39 -0500, Data _null_; <iebupdte@GMAIL.COM> wrote: >> >> >On 9/22/09, Daniel <daniel.biostatistics@gmail.com> wrote: >> >> this means that I need to have to create a dataset with my original >> >> data repeated X times, each time with a new value of REPLICATE >> > >> >METHOD=URS does NOT produce the data the that I think the OP is >> >requesting. If I understand correctly he wants to replicate the >> >original data set REP=n times. >> > >> >Similar to this but with less work. >> > >> >data class10; >> > set >> > sashelp.class(in=in1 ) >> > sashelp.class(in=in2 ) >> > sashelp.class(in=in3 ) >> > sashelp.class(in=in4 ) >> > sashelp.class(in=in5 ) >> > sashelp.class(in=in6 ) >> > sashelp.class(in=in7 ) >> > sashelp.class(in=in8 ) >> > sashelp.class(in=in9 ) >> > sashelp.class(in=in10) open=defer; >> > replicate = index(cats(of in:),'1'); >> > run; >> > >> > >> >Using URS does not do that produce that same result. >> > >> >2048 proc surveyselect method=urs rate=1 rep=10 data=sashelp.class >> >out=class10; >> >2049 run; >> > >> >NOTE: The data set WORK.CLASS10 has 124 observations and 7 variables. >> > >> > >> >On 9/22/09, oloolo <dynamicpanel@yahoo.com> wrote: >> >> in addition to what DATA _NULL_ said, be sure to use: >> >> method=urs >> >> to get a random sample WITH REPLACEMENT >> >> you can set other values for "rate=", say rate=0.7 >> >> >> >> proc surveyselect data=yourdata out=sample >> >> rate=1 method=urs rep=100; >> >> run; >> >> >> >> On Tue, 22 Sep 2009 10:01:24 -0500, Data _null_; <iebupdte@GMAIL.COM> >> wrote: >> >> >> >> >Consider a SURVEYSELECT with RATE=1. This is in one of Cassel's paper >> >> >but you may have missed it. >> >> > >> >> >2042 proc surveyselect rate=1 rep=10 data=sashelp.class out=class10; >> >> >2043 run; >> >> > >> >> >NOTE: Under the specified sampling rate, all units will be included in >> >> >the sample. >> >> >NOTE: The data set WORK.CLASS10 has 190 observations and 6 variables. >> >> > >> >> > >> >> > >> >> >On 9/22/09, Daniel <daniel.biostatistics@gmail.com> wrote: >> >> >> Good morning All, >> >> >> >> >> >> I am developing a predictive model (outcome binary) following the >> >> >> methodology outlined in "Clinical prediction models" by Steyerberg, or >> >> >> that in StatMed vol. 15 pp. 361-387 (Multivariable prognostic models: >> >> >> Issues in developing models, evaluating assumtions and adequacy, and >> >> >> measuring and reducing errors). I am using bootstrap to obtain >> >> >> measures of shrinkage and optimism to correct my regression >> >> >> coefficients and goodness of fit (GOF) measures (respectively) for >> >> >> overfitting. The steps include: >> >> >> >> >> >> 1. Obtain X bootstrap samples with replacement, of the same size as >> >> >> the original data >> >> >> 2. Use each sample to model the outcome using, in our case, a fixed >> >> >> set of covariates. Get GOF measures of interest >> >> >> 3. Score the original data with the model obtained in 2. Obtain GOF >> >> >> measures of interest on the model applied to the original data >> >> >> ... some additional steps irrelevant to my question >> >> >> >> >> >> I've used David Cassell's advice to program, in very few lines, steps >> >> >> 1 and 2, by building a dataset with my X bootstrap samples with >> >> >> replacement, and then running PROC LOGISTIC with the "BY REPLICATE" >> >> >> statement. >> >> >> >> >> >> To score the original data using each of my X models, I used the >> >> >> OUTEST= option in my PROC LOGISTIC run of step 2, and I then run a >> >> >> second PROC LOGISTIC, this time with the INEST= option. But for this >> >> >> to work the way I want, I need to use a "BY REPLICATE" statement and >> >> >> this means that I need to have to create a dataset with my original >> >> >> data repeated X times, each time with a new value of REPLICATE. This >> >> >> allows me to avoid the do loop. The negative aspect (though it might >> >> >> be mitigated by the efficiency of using the BY statement) is that I >> >> >> need to create this dataset and depending on the value of X, it can >> >> >> get quite large. Can you think of other ways this could be done as >> >> >> efficiently as steps 1 and 2 (perhaps from your own experiences)? >> >> >> >> >> >> Thank you. >> >> >> >> >> >> Daniel >> >> >> >> >> >>