I have a data set containing 980 paired observations of fish length and age. I would like to use a bootstrapping approach to examine how sample size affects the precision of model parameter estimates. I have used the following program to successfully create a dataset where 3 fish per cm length class are selected 1000 times from the original dataset: PROC SURVEYSELECT DATA = AGE OUT = SAMPLE METHOD = URS N = 3 SEED = 9876 OUTHITS REP = 1000; STRATA TLINT; RUN; Next I fit model parameters to each replicate in this dataset: PROC SORT DATA = SAMPLE; BY REPLICATE; RUN; PROC NLIN DATA = SAMPLE; PARMS LINF = 550 K = .25 t0 = 0.1; MODEL TL = LINF*(1-EXP(-K*(AGE-t0))); BY REPLICATE; OUTPUT OUT = FITTED; RUN; I would like to create a dataset that contains parameter estimates for each replicate. The dataset would contain the following variables: REPLICATE LINF K t0 and would look like this, for example: 1 568 .25 .02 2 520 .27 .14 3 491 .32 .01 etc. I have also attached the SAS file. Any help would be appreciated.
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