2.........Mixed model fitting................ ......Block effects and genotype effects assumed fixed.......... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 2.000 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 31.60 9.92 4.30 2.92 1.89 Predictions from REML analysis ------------------------------ Response variate: GYld Predictions Geno 1 2 3 4 5 6 7 9.00 8.00 13.00 10.00 11.00 13.00 8.00 Standard errors Geno 1 2 3 4 5 6 7 1.106 1.106 1.106 1.106 2.028 2.028 2.028 Standard error of differences Geno 1 1 * Geno 2 2 1.633 * Geno 3 3 1.633 1.633 * Geno 4 4 1.633 1.633 1.633 * Geno 5 5 2.160 2.160 2.449 2.449 * Geno 6 6 2.160 2.160 2.449 2.449 2.309 * Geno 7 7 2.449 2.160 2.160 2.449 2.944 2.944 * 1 2 3 4 5 6 7 Standard errors of differences Average: 2.174 Maximum: 2.944 Minimum: 1.633 3.........Mixed model fitting................ ......Block effects and genotype effects assumed random................... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 11.00 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 4.437 3.106 2.201 1.796 1.363 Predictions from REML analysis ------------------------------ Response variate: GYld Predictions Geno 1 2 3 4 5 6 7 8.78 8.44 12.40 10.40 9.93 11.05 9.13 Standard errors Geno 1 2 3 4 5 6 7 1.194 1.201 1.190 1.185 1.555 1.555 1.548 Standard error of differences Geno 1 1 * Geno 2 2 1.255 * Geno 3 3 1.245 1.252 * Geno 4 4 1.252 1.249 1.255 * Geno 5 5 1.500 1.491 1.587 1.598 * Geno 6 6 1.500 1.491 1.587 1.598 1.640 * Geno 7 7 1.587 1.485 1.500 1.602 1.790 1.790 * 1 2 3 4 5 6 7 Standard errors of differences Average: 1.488 Maximum: 1.790 Minimum: 1.245 2.........Mixed model fitting................ ......Block effects and genotype effects assumed fixed.......... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 2.000 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 31.60 9.92 4.30 2.92 1.89 Predictions from REML analysis ------------------------------ Response variate: HSW Predictions Geno 1 2 3 4 5 6 7 19.97 19.20 23.50 21.72 22.49 24.49 19.45 Standard errors Geno 1 2 3 4 5 6 7 1.306 1.306 1.306 1.306 2.395 2.395 2.395 Standard error of differences Geno 1 1 * Geno 2 2 1.929 * Geno 3 3 1.929 1.929 * Geno 4 4 1.929 1.929 1.929 * Geno 5 5 2.551 2.551 2.893 2.893 * Geno 6 6 2.551 2.551 2.893 2.893 2.727 * Geno 7 7 2.893 2.551 2.551 2.893 3.477 3.477 * 1 2 3 4 5 6 7 Standard errors of differences Average: 2.567 Maximum: 3.477 Minimum: 1.929 3.........Mixed model fitting................ ......Block effects and genotype effects assumed random................... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 11.00 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 4.437 3.106 2.201 1.796 1.363 Predictions from REML analysis ------------------------------ Response variate: HSW Predictions Geno 1 2 3 4 5 6 7 19.92 19.60 23.01 21.95 21.12 22.09 20.54 Standard errors Geno 1 2 3 4 5 6 7 1.218 1.226 1.213 1.207 1.563 1.563 1.555 Standard error of differences Geno 1 1 * Geno 2 2 1.307 * Geno 3 3 1.298 1.304 * Geno 4 4 1.304 1.301 1.307 * Geno 5 5 1.533 1.524 1.608 1.617 * Geno 6 6 1.533 1.524 1.608 1.617 1.670 * Geno 7 7 1.606 1.518 1.532 1.621 1.791 1.791 * 1 2 3 4 5 6 7 Standard errors of differences Average: 1.520 Maximum: 1.791 Minimum: 1.298 2.........Mixed model fitting................ ......Block effects and genotype effects assumed fixed.......... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 2.000 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 31.60 9.92 4.30 2.92 1.89 Predictions from REML analysis ------------------------------ Response variate: GYld Predictions Geno 1 2 3 4 5 6 7 9.00 8.00 13.00 10.00 11.00 13.00 8.00 Standard errors Geno 1 2 3 4 5 6 7 1.106 1.106 1.106 1.106 2.028 2.028 2.028 Standard error of differences Geno 1 1 * Geno 2 2 1.633 * Geno 3 3 1.633 1.633 * Geno 4 4 1.633 1.633 1.633 * Geno 5 5 2.160 2.160 2.449 2.449 * Geno 6 6 2.160 2.160 2.449 2.449 2.309 * Geno 7 7 2.449 2.160 2.160 2.449 2.944 2.944 * 1 2 3 4 5 6 7 Standard errors of differences Average: 2.174 Maximum: 2.944 Minimum: 1.633 3.........Mixed model fitting................ ......Block effects and genotype effects assumed random................... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 11.00 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 4.437 3.106 2.201 1.796 1.363 Predictions from REML analysis ------------------------------ Response variate: GYld Predictions Geno 1 2 3 4 5 6 7 8.78 8.44 12.40 10.40 9.93 11.05 9.13 Standard errors Geno 1 2 3 4 5 6 7 1.194 1.201 1.190 1.185 1.555 1.555 1.548 Standard error of differences Geno 1 1 * Geno 2 2 1.255 * Geno 3 3 1.245 1.252 * Geno 4 4 1.252 1.249 1.255 * Geno 5 5 1.500 1.491 1.587 1.598 * Geno 6 6 1.500 1.491 1.587 1.598 1.640 * Geno 7 7 1.587 1.485 1.500 1.602 1.790 1.790 * 1 2 3 4 5 6 7 Standard errors of differences Average: 1.488 Maximum: 1.790 Minimum: 1.245 2.........Mixed model fitting................ ......Block effects and genotype effects assumed fixed.......... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 2.000 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 31.60 9.92 4.30 2.92 1.89 Predictions from REML analysis ------------------------------ Response variate: HSW Predictions Geno 1 2 3 4 5 6 7 20.52 18.60 24.78 21.60 21.26 25.36 18.89 Standard errors Geno 1 2 3 4 5 6 7 0.5899 0.5899 0.5899 0.5899 1.0818 1.0818 1.0818 Standard error of differences Geno 1 1 * Geno 2 2 0.871 * Geno 3 3 0.871 0.871 * Geno 4 4 0.871 0.871 0.871 * Geno 5 5 1.153 1.153 1.307 1.307 * Geno 6 6 1.153 1.153 1.307 1.307 1.232 * Geno 7 7 1.307 1.153 1.153 1.307 1.571 1.571 * 1 2 3 4 5 6 7 Standard errors of differences Average: 1.160 Maximum: 1.571 Minimum: 0.8713 3.........Mixed model fitting................ ......Block effects and genotype effects assumed random................... LSD (least signficant difference) at an alpha probability level = t-value * Standard error of difference The following gives two tailed t-value corresponding to a given alpha(%) and the error df Error Degrees of Freedom = 11.00 Alpha 0.1 1.0 5.0 10.0 20.0 t_value 4.437 3.106 2.201 1.796 1.363 Predictions from REML analysis ------------------------------ Response variate: HSW Predictions Geno 1 2 3 4 5 6 7 20.35 18.76 24.67 21.73 20.92 24.53 19.45 Standard errors Geno 1 2 3 4 5 6 7 1.134 1.136 1.134 1.133 1.407 1.407 1.406 Standard error of differences Geno 1 1 * Geno 2 2 0.859 * Geno 3 3 0.854 0.857 * Geno 4 4 0.857 0.856 0.859 * Geno 5 5 1.105 1.101 1.224 1.229 * Geno 6 6 1.105 1.101 1.224 1.229 1.199 * Geno 7 7 1.225 1.100 1.106 1.232 1.446 1.446 * 1 2 3 4 5 6 7 Standard errors of differences Average: 1.105 Maximum: 1.446 Minimum: 0.8541