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If you are working with a very large data set and you find that running procedures takes a while, you can use the maxobs = option on the proc statement of all analysis procedures to limit the number of observations that are read in. This can be very useful when you are debugging a program. Just remember to delete that option when you have the programming working correctly. Compare the results of the two proc reg calls below.
proc regress data=temp1 filetype=sas design = jackknife maxobs = 1000; weight rakedw0; jackwgts rakedw1--rakedw80 / adjjack=1; model ae13 = ae14; run;
S U D A A N
Software for the Statistical Analysis of Correlated Data
Copyright Research Triangle Institute January 2003
Release 8.0.2
Number of observations read : 1000 Weighted count: 431947
Observations used in the analysis : 591 Weighted count: 242364
Denominator degrees of freedom : 80
Maximum number of estimable parameters for the model is 2
Weighted mean response is 2.262239
Multiple R-Square for the dependent variable AE13: 0.216196
Variance Estimation Method: Replicate Weight Jackknife
Working Correlations: Independent
Link Function: Identity
Response variable AE13: AE13
----------------------------------------------------------------------
Independent P-value
Variables and Beta T-Test
Effects Coeff. SE Beta T-Test B=0 B=0
----------------------------------------------------------------------
Intercept 1.96 0.11 17.83 0.0000
AE14 0.32 0.08 3.78 0.0003
----------------------------------------------------------------------
-------------------------------------------------------
Contrast Degrees
of P-value
Freedom Wald F Wald F
-------------------------------------------------------
OVERALL MODEL 2 197.90 0.0000
MODEL MINUS
INTERCEPT 1 14.29 0.0003
INTERCEPT 1 317.85 0.0000
AE14 1 14.29 0.0003
-------------------------------------------------------
proc regress data=temp1 filetype=sas design = jackknife; weight rakedw0; jackwgts rakedw1--rakedw80 / adjjack=1; model ae13 = ae14; run;
S U D A A N
Software for the Statistical Analysis of Correlated Data
Copyright Research Triangle Institute January 2003
Release 8.0.2
Number of observations read : 55428 Weighted count: 23847415
Observations used in the analysis : 32538 Weighted count: 13783845
Denominator degrees of freedom : 80
Maximum number of estimable parameters for the model is 2
Weighted mean response is 2.188590
Multiple R-Square for the dependent variable AE13: 0.241897
Variance Estimation Method: Replicate Weight Jackknife
Working Correlations: Independent
Link Function: Identity
Response variable AE13: AE13
----------------------------------------------------------------------
Independent P-value
Variables and Beta T-Test
Effects Coeff. SE Beta T-Test B=0 B=0
----------------------------------------------------------------------
Intercept 1.88 0.01 152.15 0.0000
AE14 0.34 0.01 25.47 0.0000
----------------------------------------------------------------------
-------------------------------------------------------
Contrast Degrees
of P-value
Freedom Wald F Wald F
-------------------------------------------------------
OVERALL MODEL 2 12818.28 0.0000
MODEL MINUS
INTERCEPT 1 648.71 0.0000
INTERCEPT 1 23150.59 0.0000
AE14 1 648.71 0.0000
-------------------------------------------------------
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