Table 3 Regression results for tie persistence using generalized linear models for the two prediction models and different thresholds for the number of calls \(\pmb{w_{ij}}\)

1.491^∗∗∗

1.440^∗∗∗

1.331^∗∗∗

2.096^∗∗∗

1.793^∗∗∗

1.367^∗∗∗

(0.021)

(0.029)

(0.045)

(0.060)

(0.072)

(0.093)

0.105^∗∗∗

0.049^∗∗

0.036

0.109^∗∗

0.131^∗∗

0.115

(0.012)

(0.019)

(0.032)

(0.034)

(0.046)

(0.067)

−0.094

−0.085^∗∗∗

−0.127^∗∗∗

−0.044^∗∗

−0.143^∗∗∗

−0.142^∗

(0.010)

(0.018)

(0.030)

(0.032)

(0.041)

(0.064)

0.241^∗∗∗

0.215^∗∗∗

0.245^∗∗∗

0.286^∗∗∗

0.340^∗∗∗

0.413^∗∗∗

(0.017)

(0.023)

(0.038)

(0.046)

(0.061)

(0.082)

0.039^∗∗

0.035

0.031

−0.026

0.032

−0.019

(0.010)

(0.018)

(0.029)

(0.033)

(0.045)

(0.066)

0.084^∗∗∗

0.109^∗∗∗

0.101^∗∗∗

0.151^∗∗

0.127^∗∗

0.147^∗

(0.012)

(0.017)

(0.029)

(0.032)

(0.041)

(0.062)

0.001

0.031

−0.008

−0.021

0.003

−0.036

(0.012)

(0.018)

(0.031)

(0.034)

(0.044)

(0.064)

0.079^∗∗∗

0.121^∗∗∗

0.189^∗∗∗

0.035^∗

0.097^∗

0.239^∗∗∗

(0.012)

(0.018)

(0.031)

(0.033)

(0.043)

(0.064)

−1.102^∗∗∗

−1.414^∗∗∗

−1.931^∗∗∗

(0.015)

(0.024)

(0.044)

−0.362^∗∗∗

−0.422^∗∗∗

−0.539^∗∗∗

−0.653^∗∗∗

−0.724^∗∗∗

−0.853^∗∗∗

(0.014)

(0.020)

(0.035)

(0.037)

(0.048)

(0.074))

0.029^∗

−0.001

0.017

0.036

−0.036

0.046

(0.014)

(0.019)

(0.033)

(0.038)

(0.048)

(0.069)

−0.310^∗∗∗

−0.282^∗∗∗

−0.307^∗∗∗

−0.316^∗∗∗

−0.290^∗∗∗

−0.269^∗∗∗

(0.013)

(0.019)

(0.034)

(0.036)

(0.048)

(0.071)

0.681^∗∗∗

0.743^∗∗∗

0.852^∗∗∗

0.779^∗∗∗

0.708^∗∗∗

0.590^∗∗∗

(0.014)

(0.021)

(0.035)

(0.039)

(0.050)

(0.070)

0.864

0.884

0.919

0.875

0.867

0.845