remission data frame: remiss cell smear infil li blast temp 1 1 0.80 0.83 0.66 1.9 1.100 0.996 2 1 0.90 0.36 0.32 1.4 0.740 0.992 3 0 0.80 0.88 0.70 0.8 0.176 0.982 4 0 1.00 0.87 0.87 0.7 1.053 0.986 5 1 0.90 0.75 0.68 1.3 0.519 0.980 6 0 1.00 0.65 0.65 0.6 0.519 0.982 7 1 0.95 0.97 0.92 1.0 1.230 0.992 8 0 0.95 0.87 0.83 1.9 1.354 1.020 9 0 1.00 0.45 0.45 0.8 0.322 0.999 10 0 0.95 0.36 0.34 0.5 0.000 1.038 11 0 0.85 0.39 0.33 0.7 0.279 0.988 12 0 0.70 0.76 0.53 1.2 0.146 0.982 13 0 0.80 0.46 0.37 0.4 0.380 1.006 14 0 0.20 0.39 0.08 0.8 0.114 0.990 15 0 1.00 0.90 0.90 1.1 1.037 0.990 16 1 1.00 0.84 0.84 1.9 2.064 1.020 17 0 0.65 0.42 0.27 0.5 0.114 1.014 18 0 1.00 0.75 0.75 1.0 1.322 1.004 19 0 0.50 0.44 0.22 0.6 0.114 0.990 20 1 1.00 0.63 0.63 1.1 1.072 0.986 21 0 1.00 0.33 0.33 0.4 0.176 1.010 22 0 0.90 0.93 0.84 0.6 1.591 1.020 23 1 1.00 0.58 0.58 1.0 0.531 1.002 24 0 0.95 0.32 0.30 1.6 0.886 0.988 25 1 1.00 0.60 0.60 1.7 0.964 0.990 26 1 1.00 0.69 0.69 0.9 0.398 0.986 27 0 1.00 0.73 0.73 0.7 0.398 0.986 Call: glm(formula = remiss ~ cell + smear + infil + li + blast + temp, family = binomial(link = "logit"), data = remission) Deviance Residuals: Min 1Q Median 3Q Max -1.95165 -0.66491 -0.04372 0.74304 1.67069 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 58.0385 71.2364 0.815 0.4152 cell 24.6615 47.8377 0.516 0.6062 smear 19.2936 57.9500 0.333 0.7392 infil -19.6013 61.6815 -0.318 0.7507 li 3.8960 2.3371 1.667 0.0955 . blast 0.1511 2.2786 0.066 0.9471 temp -87.4339 67.5735 -1.294 0.1957 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 34.372 on 26 degrees of freedom Residual deviance: 21.751 on 20 degrees of freedom AIC: 35.751 Number of Fisher Scoring iterations: 8 Backward Selection: Start: AIC=35.75 remiss ~ cell + smear + infil + li + blast + temp Df Deviance AIC - blast 1 21.755 33.755 - infil 1 21.857 33.857 - smear 1 21.869 33.869 - cell 1 22.071 34.071 21.751 35.751 - temp 1 23.877 35.877 - li 1 26.095 38.095 Step: AIC=33.76 remiss ~ cell + smear + infil + li + temp Df Deviance AIC - infil 1 21.858 31.858 - smear 1 21.869 31.869 - cell 1 22.073 32.073 21.755 33.755 - temp 1 24.198 34.199 - li 1 30.216 40.216 Step: AIC=31.86 remiss ~ cell + smear + li + temp Df Deviance AIC - smear 1 21.953 29.953 21.858 31.858 - temp 1 24.292 32.292 - cell 1 24.477 32.477 - li 1 30.434 38.434 Step: AIC=29.95 remiss ~ cell + li + temp Df Deviance AIC 21.953 29.953 - temp 1 24.341 30.341 - cell 1 24.648 30.648 - li 1 30.829 36.829 Call: glm(formula = remiss ~ cell + li + temp, family = binomial(link = "logit"), data = remission) Deviance Residuals: Min 1Q Median 3Q Max -2.02043 -0.66313 -0.08323 0.81282 1.65887 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) 67.634 56.888 1.189 0.2345 cell 9.652 7.751 1.245 0.2130 li 3.867 1.778 2.175 0.0297 * temp -82.074 61.712 -1.330 0.1835 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 34.372 on 26 degrees of freedom Residual deviance: 21.953 on 23 degrees of freedom AIC: 29.953 Number of Fisher Scoring iterations: 7 Predicted Values and Prediction Intevals: 1 2 3 4 5 6 0.7226489149 0.5787391222 0.1045989532 0.2825773423 0.7141804031 0.2708868370 7 8 9 10 11 12 0.3215553922 0.6072319482 0.1663164092 0.0015692660 0.0728519988 0.1728569527 13 14 15 16 17 18 0.0034574901 0.0001849908 0.5712204214 0.7146954319 0.0006223086 0.2228887597 19 20 21 22 23 24 0.0015425200 0.6491095138 0.0169296604 0.0062175249 0.2526056942 0.8701089351 25 26 27 0.9313166404 0.4605092266 0.2825773423