============================================================================ Summary statistics for the phylogenetic generalized least squares regression ============================================================================ cB ~ cSh Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.53874 -0.05754 0.01902 0.11697 1.25317 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.27253 0.73557 1.7300 0.084887 . cSh1 -0.47388 0.17483 -2.7105 0.007191 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.1841 on 246 degrees of freedom Multiple R-squared: 0.029, Adjusted R-squared: 0.02505 F-statistic: 7.347 on 1 and 246 DF, p-value: 0.007191 cB ~ cSu Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.90199 -0.08024 0.00420 0.10087 1.28719 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.10665 0.69030 1.6032 0.11000 cSu1 -0.33333 0.16330 -2.0412 0.04215 * cSu2 -0.13230 0.15224 -0.8690 0.38558 cSu3 -0.21839 0.26128 -0.8358 0.40393 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.1787 on 288 degrees of freedom Multiple R-squared: 0.01949, Adjusted R-squared: 0.009275 F-statistic: 1.908 on 3 and 288 DF, p-value: 0.1284 cB ~ rD Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.67316 -0.09286 0.00000 0.09592 1.05426 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 1.05981 0.71887 1.4743 0.1414 rD1 0.48250 0.20340 2.3721 0.0183 * --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.1871 on 307 degrees of freedom Multiple R-squared: 0.018, Adjusted R-squared: 0.0148 F-statistic: 5.627 on 1 and 307 DF, p-value: 0.0183 cB ~ lH Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.67316 -0.08845 0.00623 0.11681 1.05426 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.991071 0.770217 1.2867 0.1992 lH0 -0.375008 0.346880 -1.0811 0.2805 lH2 0.117630 0.362626 0.3244 0.7459 lH3 -0.053874 0.172070 -0.3131 0.7544 lH4 0.470323 0.339812 1.3841 0.1674 lH7 0.190134 0.404981 0.4695 0.6391 lH8 -0.072939 0.257995 -0.2827 0.7776 Residual standard error: 0.1894 on 300 degrees of freedom Multiple R-squared: 0.01434, Adjusted R-squared: -0.00537 F-statistic: 0.7276 on 6 and 300 DF, p-value: 0.6277 cSh ~ cSu Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.63365 -0.01432 0.00097 0.02613 0.17819 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.148343 0.272017 0.5453 0.5860 cSu1 -0.086467 0.063008 -1.3723 0.1713 cSu2 0.032648 0.056008 0.5829 0.5605 cSu3 -0.032250 0.102786 -0.3138 0.7540 Residual standard error: 0.06771 on 233 degrees of freedom Multiple R-squared: 0.03082, Adjusted R-squared: 0.01834 F-statistic: 2.47 on 3 and 233 DF, p-value: 0.06266 cSh ~ rD Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.51116 -0.01297 0.00000 0.01508 0.36235 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.134216 0.266610 0.5034 0.6151 rD1 -0.100660 0.074521 -1.3508 0.1780 Residual standard error: 0.06676 on 247 degrees of freedom Multiple R-squared: 0.007333, Adjusted R-squared: 0.003314 F-statistic: 1.825 on 1 and 247 DF, p-value: 0.178 cSh ~ lH Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.36235 -0.01607 0.00000 0.02029 0.51116 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.1184065 0.2777522 0.4263 0.670268 lH0 0.3728986 0.1315927 2.8337 0.004991 ** lH2 0.0096628 0.1291157 0.0748 0.940406 lH3 0.0871163 0.0663195 1.3136 0.190235 lH4 -0.2078700 0.1262380 -1.6467 0.100933 lH7 -0.1364991 0.1452376 -0.9398 0.348244 lH8 0.0118965 0.1024344 0.1161 0.907640 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.06581 on 241 degrees of freedom Multiple R-squared: 0.05877, Adjusted R-squared: 0.03534 F-statistic: 2.508 on 6 and 241 DF, p-value: 0.02257 cSu ~ rD Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.83550 -0.09047 -0.00001 0.08539 0.65284 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.42475 0.68072 0.6240 0.5331 rD1 0.34100 0.20087 1.6976 0.0906 . --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.1768 on 307 degrees of freedom Multiple R-squared: 0.0093, Adjusted R-squared: 0.006073 F-statistic: 2.882 on 1 and 307 DF, p-value: 0.0906 cSu ~ lH Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.81508 -0.07795 0.01260 0.10089 0.75365 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.513333 0.744834 0.6892 0.4912 lH0 -0.384598 0.358044 -1.0742 0.2836 lH2 -0.049112 0.356172 -0.1379 0.8904 lH3 -0.131732 0.163491 -0.8057 0.4210 lH4 0.046383 0.319400 0.1452 0.8846 lH7 -0.350817 0.431361 -0.8133 0.4167 lH8 0.246951 0.215812 1.1443 0.2534 Residual standard error: 0.1819 on 301 degrees of freedom Multiple R-squared: 0.02172, Adjusted R-squared: 0.002222 F-statistic: 1.114 on 6 and 301 DF, p-value: 0.354 rD ~ lH Call: pgls(formula = form.gls, data = comp.data, param.CI = 0.999) Residuals: Min 1Q Median 3Q Max -0.237369 -0.013120 0.000097 0.019886 0.185350 Branch length transformations: kappa [Fix] : 1.000 lambda [Fix] : 1.000 delta [Fix] : 1.000 Coefficients: Estimate Std. Error t value Pr(>|t|) (Intercept) 0.066619 0.220179 0.3026 0.76241 lH0 -0.043551 0.097681 -0.4459 0.65600 lH2 -0.070042 0.103658 -0.6757 0.49970 lH3 0.093564 0.045781 2.0437 0.04178 * lH4 -0.025516 0.090134 -0.2831 0.77728 lH7 -0.071206 0.116195 -0.6128 0.54042 lH8 0.075060 0.062803 1.1952 0.23288 --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 Residual standard error: 0.05445 on 330 degrees of freedom Multiple R-squared: 0.01749, Adjusted R-squared: -0.0003727 F-statistic: 0.9791 on 6 and 330 DF, p-value: 0.4392