Summary of diabetes data set analysis: Variable names Variable Original Obs name name 1 x1 age 2 x2 sex 3 x3 bmi 4 x4 bp 5 x5 s1 6 x6 s2 7 x7 s3 8 x8 s4 9 x9 s5 10 x10 s6 11 y y 1+S Strong No hier Weak No hier No hier Weak Main Adj=iter Adj=seq Adj=seq Only 1 Intercept Intercept Intercept Intercept Intercept Intercept Intercept 2 x3 x3 x3 x3 x3 x3 x3 3 x9 x9 x9 x9 x9 x9 x9 4 x4 x4 x4 x4 x4 x4 x4 5 x5 x1*x2 x5 x5 x5 x5 x5 6 x3*x4 x3*x4 x3*x4 x1*x2 x1*x2 x3*x4 x2 7 x6 x7 x6 x2 x2 x6 x6 8 x2 x2 x2 x6 x6 x2 x2*x1 x3*x4 x3*x4 x2*x1 ahat 0.0174 0.0070 0.0098 0.0505 0.0505 0.0507 0.0875 R^2 0.53 0.53 0.54 0.54 0.54 0.54 0.51 %fsr_linear(dataset=diabetes,model=age--s6 @q,gamma=0.05,y=y,method=1); method=1 strong Forward Sequence Selection Effect p-to- monotonized Obs Step 1+S Entered enter p-to-enter 1 0 1 Intercept <.0001 0.00000 2 1 2 x3 <.0001 0.00000 3 2 3 x9 <.0001 0.00000 4 3 4 x4 <.0001 0.00004 5 4 5 x5 0.0015 0.00145 6 5 6 x3*x4 0.0074 0.00739 7 6 7 x6 0.0049 0.00739 8 7 8 x2 0.0001 0.00739 9 8 9 x2*x4 0.0437 0.04373 10 9 10 x10 0.2254 0.22535 11 10 11 x10*x10 0.0238 0.22535 12 11 12 x4*x10 0.1451 0.22535 13 12 13 x4*x5 0.2825 0.28252 14 13 14 x4*x6 0.2767 0.28252 15 14 15 x6*x9 0.3571 0.35713 16 15 16 x3*x5 0.3515 0.35713 17 16 17 x3*x6 0.3244 0.35713 18 17 18 x3*x9 0.3593 0.35929 19 18 19 x6*x6 0.4200 0.42003 20 19 20 x2*x6 0.5225 0.52246 21 20 21 x2*x5 0.2477 0.52246 22 21 22 x2*x9 0.3683 0.52246 23 22 23 x2*x10 0.3599 0.52246 24 23 24 x2*x3 0.4277 0.52246 25 24 25 x9*x10 0.5832 0.58323 26 25 26 x7 0.3868 0.58323 27 26 27 x9*x9 0.0101 0.58323 28 27 28 x7*x7 0.2336 0.58323 29 28 29 x3*x7 0.1655 0.58323 30 29 30 x5*x9 0.3503 0.58323 Sequence of Possible Models Obs alpha gammahat 1+S 1 0.00000 0.00000 1 2 0.00000 0.00000 2 3 0.00000 0.00000 3 4 0.00004 0.00009 4 5 0.00145 0.00349 5 6 0.00739 0.01663 8 7 0.04373 0.10689 9 8 0.22535 0.48826 12 9 0.28252 0.48432 14 10 0.35713 0.44116 17 11 0.35929 0.39921 18 12 0.42003 0.42003 19 13 0.52246 0.30477 24 14 0.58323 0.19915 41 15 0.58936 0.16447 43 16 0.61784 0.15446 44 17 0.63798 0.14177 45 18 0.72007 0.14088 46 19 0.72675 0.07268 50 20 0.76639 0.05026 61 21 0.85344 0.02709 63 22 0.87414 0.01366 64 23 0.88485 0.00000 65 Fast FSR estimates alpha Obs estimate 1+S 1 0.017391 8 method=2 no hier Forward Sequence Selection Effect p-to- monotonized Obs Step 1+S Entered enter p-to-enter 1 0 1 Intercept <.0001 0.00000 2 1 2 x3 <.0001 0.00000 3 2 3 x9 <.0001 0.00000 4 3 4 x4 <.0001 0.00004 5 4 5 x1*x2 0.0003 0.00026 6 5 6 x3*x4 0.0021 0.00208 7 6 7 x7 0.0029 0.00286 8 7 8 x2 <.0001 0.00286 9 8 9 x10*x10 0.0192 0.01917 10 9 10 x1*x1 0.1091 0.10906 11 10 11 x4*x10 0.1705 0.17050 12 11 12 x5 0.1507 0.17050 13 12 13 x6 0.0564 0.17050 14 13 14 x9*x9 0.0015 0.17050 15 14 15 x1*x6 0.1877 0.18771 16 15 16 x1*x5 0.0790 0.18771 17 16 17 x2*x4 0.1803 0.18771 18 17 18 x10 0.2285 0.22851 19 18 19 x8 0.3084 0.30836 20 19 20 x2*x8 0.2199 0.30836 Sequence of Possible Models Obs alpha gammahat 1+S 1 0.00000 0.00000 1 2 0.00000 0.00000 2 3 0.00000 0.00000 3 4 0.00004 0.00057 4 5 0.00026 0.00311 5 6 0.00208 0.02041 6 7 0.00286 0.02037 8 8 0.01917 0.11927 9 9 0.10906 0.59985 10 10 0.17050 0.62110 14 11 0.18771 0.53000 17 12 0.22851 0.59666 18 13 0.30836 0.69382 20 Fast FSR estimates Estimate Obs for alpha 1+S 1 .007017544 8 method=3 weak hier Forward Sequence Selection Effect p-to- monotonized Obs Step 1+S Entered enter p-to-enter 1 0 1 Intercept <.0001 0.00000 2 1 2 x3 <.0001 0.00000 3 2 3 x9 <.0001 0.00000 4 3 4 x4 <.0001 0.00004 5 4 5 x5 0.0015 0.00145 6 5 6 x3*x4 0.0074 0.00739 7 6 7 x6 0.0049 0.00739 8 7 8 x2 0.0001 0.00739 9 8 9 x2*x1 0.0006 0.00739 10 9 10 x9*x10 0.0383 0.03827 11 10 11 x9*x1 0.1908 0.19083 12 11 12 x10 0.2503 0.25031 13 12 13 x10*x10 0.0873 0.25031 14 13 14 x4*x10 0.2085 0.25031 15 14 15 x4*x2 0.2376 0.25031 16 15 16 x4*x7 0.1220 0.25031 17 16 17 x6*x1 0.2254 0.25031 18 17 18 x9*x6 0.2245 0.25031 19 18 19 x5*x8 0.0785 0.25031 20 19 20 x6*x8 0.1421 0.25031 Sequence of Possible Models Obs alpha gammahat 1+S 1 0.00000 0.00000 1 2 0.00000 0.00000 2 3 0.00000 0.00000 3 4 0.00004 0.00024 4 5 0.00145 0.00960 5 6 0.00739 0.03778 9 7 0.03827 0.17223 10 8 0.19083 0.76331 11 9 0.25031 0.48810 20 Fast FSR estimates alpha Obs estimate 1+S 1 .009782609 9 method=4 no hier adj=1 Forward Sequence monotonized Selection Effect p-to- adjusted adjusted Obs Step 1+S Entered enter p-to-enter p-to-enter 1 0 1 Intercept <.0001 0.00000 0.00000 2 1 2 x3 <.0001 0.00000 0.00000 3 2 3 x9 <.0001 0.00000 0.00000 4 3 4 x4 <.0001 0.00004 0.00004 5 4 5 x5 0.0015 0.00145 0.00145 6 5 6 x1*x2 0.0005 0.00580 0.00580 7 6 7 x2 0.0053 0.00535 0.00580 8 7 8 x6 0.0004 0.00043 0.00580 9 8 9 x3*x4 0.0019 0.02058 0.02058 10 9 10 x10*x10 0.0088 0.09293 0.09293 11 10 11 x10 0.3368 0.33676 0.33676 12 11 12 x8 0.5417 0.54165 0.54165 13 12 13 x7 0.4065 0.40653 0.54165 14 13 14 x9*x9 0.0010 0.01071 0.54165 15 14 15 x1 0.7914 0.79141 0.79141 16 15 16 x1*x1 0.0923 0.97876 0.97876 17 16 17 x4*x10 0.2166 2.29600 2.29600 18 17 18 x4*x2 0.1976 2.09403 2.29600 19 18 19 x4*x7 0.1786 1.89357 2.29600 20 19 20 x2*x8 0.2255 2.38994 2.38994 Sequence of Possible Models Obs alpha gammahat 1+S 1 0.00000 0.00000 1 2 0.00000 0.00000 2 3 0.00000 0.00000 3 4 0.00004 0.00011 4 5 0.00145 0.00323 5 6 0.00580 0.00652 8 7 0.02058 0.02036 9 8 0.09293 0.08188 10 9 0.33676 0.23914 11 10 0.54165 0.22119 14 11 0.79141 0.24887 15 12 0.97876 0.28278 16 13 2.29600 0.52441 19 14 2.38994 0.50730 20 Fast FSR estimates alpha Obs estimate c 1+S 1 0.050530 10.6 9 method=5 no hier adj=2 Forward Sequence monotonized Selection Effect p-to- adjusted adjusted Obs Step 1+S Entered enter c p-to-enter p-to-enter 1 0 1 Intercept <.0001 5.0000 0.0000 0.0000 2 1 2 x3 <.0001 5.0000 0.0000 0.0000 3 2 3 x9 <.0001 5.5000 0.0000 0.0000 4 3 4 x4 <.0001 6.1111 0.0000 0.0000 5 4 5 x5 0.0015 6.8750 0.0015 0.0015 6 5 6 x1*x2 0.0005 7.8571 0.0043 0.0043 7 6 7 x2 0.0053 7.7143 0.0053 0.0053 8 7 8 x6 0.0004 9.0000 0.0004 0.0053 9 8 9 x3*x4 0.0019 10.8000 0.0210 0.0210 10 9 10 x10*x10 0.0088 10.6000 0.0929 0.0929 11 10 11 x10 0.3368 10.4000 0.3368 0.3368 12 11 12 x8 0.5417 13.0000 0.5417 0.5417 13 12 13 x7 0.4065 17.3333 0.4065 0.5417 14 13 14 x9*x9 0.0010 26.0000 0.0263 0.5417 15 14 15 x1 0.7914 25.5000 0.7914 0.7914 16 15 16 x1*x1 0.0923 51.0000 4.7092 4.7092 17 16 17 x4*x10 0.2166 50.0000 10.8302 10.8302 18 17 18 x4*x2 0.1976 49.0000 9.6800 10.8302 19 18 19 x4*x7 0.1786 48.0000 8.5746 10.8302 20 19 20 x2*x8 0.2255 47.0000 10.5969 10.8302 Sequence of Possible Models Obs alpha c gammahat 1+S 1 0.0000 5.0000 0.00000 1 2 0.0000 5.0000 0.00000 2 3 0.0000 5.5000 0.00000 3 4 0.0000 6.1111 0.00015 4 5 0.0015 6.8750 0.00403 5 6 0.0043 7.8571 0.00913 6 7 0.0053 9.0000 0.00661 8 8 0.0210 10.8000 0.02053 9 9 0.0929 10.6000 0.08188 10 10 0.3368 10.4000 0.24197 11 11 0.5417 26.0000 0.11309 14 12 0.7914 25.5000 0.10345 15 13 4.7092 51.0000 0.28278 16 14 10.8302 47.0000 0.51847 20 Fast FSR estimates alpha Obs estimate 1+S 1 0.050530 9 method=6 weak hier adj=2 Forward Sequence monotonized Selection Effect p-to- adjusted adjusted Obs Step 1+S Entered enter c p-to-enter p-to-enter 1 0 1 Intercept <.0001 5.0000 0.00000 0.00000 2 1 2 x3 <.0001 5.0000 0.00000 0.00000 3 2 3 x9 <.0001 1.1000 0.00000 0.00000 4 3 4 x4 <.0001 2.2222 0.00004 0.00004 5 4 5 x5 0.0015 3.5000 0.00145 0.00145 6 5 6 x3*x4 0.0074 5.0000 0.03696 0.03696 7 6 7 x6 0.0049 4.8571 0.00494 0.03696 8 7 8 x2 0.0001 6.6667 0.00012 0.03696 9 8 9 x2*x1 0.0006 8.8000 0.00514 0.03696 10 9 10 x9*x10 0.0383 8.6000 0.32916 0.32916 11 10 11 x9*x1 0.1908 8.4000 1.60296 1.60296 12 11 12 x10 0.2503 8.2000 0.25031 1.60296 13 12 13 x10*x10 0.0873 11.2500 0.98159 1.60296 14 13 14 x4*x10 0.2085 11.0000 2.29389 2.29389 15 14 15 x4*x2 0.2376 10.7500 2.55368 2.55368 16 15 16 x4*x7 0.1220 10.5000 1.28100 2.55368 17 16 17 x6*x1 0.2254 10.2500 2.31076 2.55368 18 17 18 x9*x6 0.2245 10.0000 2.24497 2.55368 19 18 19 x5*x8 0.0785 9.7500 0.76511 2.55368 20 19 20 x6*x8 0.1421 9.5000 1.34965 2.55368 Sequence of Possible Models Obs alpha c gammahat 1+S 1 0.00000 5.0000 0.00000 1 2 0.00000 5.0000 0.00000 2 3 0.00000 1.1000 0.00000 3 4 0.00004 2.2222 0.00015 4 5 0.00145 3.5000 0.00399 5 6 0.03696 8.8000 0.03603 9 7 0.32916 8.6000 0.28859 10 8 1.60296 11.2500 0.84121 13 9 2.29389 11.0000 1.11715 14 10 2.55368 9.5000 0.86691 20 Fast FSR estimates alpha Obs estimate 1+S 1 0.050654 9 method=7 main effects only Forward Sequence Selection Effect p-to- monotonized Obs Step 1+S Entered enter p-to-enter 1 0 1 Intercept <.0001 0.00000 2 1 2 x3 <.0001 0.00000 3 2 3 x9 <.0001 0.00000 4 3 4 x4 <.0001 0.00004 5 4 5 x5 0.0015 0.00145 6 5 6 x2 0.0092 0.00923 7 6 7 x6 0.0003 0.00923 8 7 8 x8 0.2619 0.26192 9 8 9 x10 0.3040 0.30401 10 9 10 x7 0.6386 0.63856 11 10 11 x1 0.8670 0.86703 Sequence of Possible Models Obs alpha gammahat 1+S 1 0.00000 0.000000 1 2 0.00000 0.000000 2 3 0.00000 0.000000 3 4 0.00004 0.000065 4 5 0.00145 0.001745 5 6 0.00923 0.005275 7 7 0.26192 0.098220 8 8 0.30401 0.067558 9 9 0.63856 0.063856 10 10 0.86703 0.000000 11 Fast FSR estimates alpha Obs estimate 1+S 1 0.0875 7 The GLM Procedure Number of Observations Read 442 Number of Observations Used 442 The GLM Procedure Dependent Variable: y y Sum of Source DF Squares Mean Square F Value Pr > F Model 6 1349515.127 224919.188 76.95 <.0001 Error 435 1271493.997 2922.975 Corrected Total 441 2621009.124 R-Square Coeff Var Root MSE y Mean 0.514884