Table 3.
Edge Model
|
||||||||
---|---|---|---|---|---|---|---|---|
Model 1 | SE | Model 2 | SE | Model 3 | SE | Model 4 | SE | |
BIC | 8,166.2395* | 7,929.2997* | 7,699.5743* | 7,689.1466* | ||||
Intercept | −2.3162* | (0.0359) | −4.3081* | (0.0362) | ||||
Mixing regular (R) | 1.1091* | (0.0430) | 1.1389* | (0.0434) | ||||
Mixing ¬ R ↔ R | 0.5560* | (0.0737) | 0.5595* | (0.0742) | ||||
Mixing ¬ R | — | — | — | — | ||||
Indiv 06 | −0.6563* | (0.0384) | ||||||
Indiv 17 | −0.9519* | (0.0397) | ||||||
Indiv 16 | −0.4602* | (0.0473) | ||||||
Indiv 37 | −0.4161* | (0.0459) | ||||||
Indiv 39 | −0.5880* | (0.0638) | ||||||
Indiv 46 | −0.7159* | (0.0502) | ||||||
Indiv 05 | 0.5852* | (0.0485) | ||||||
Indiv 07 | −0.5901* | (0.0475) | ||||||
Indiv 20 | −0.8542* | (0.0497) | ||||||
Indiv 40 | 0.7993* | (0.0552) | ||||||
Indiv 15 | −2.8539* | (0.0485) | ||||||
Indiv 19 | 0.3049* | (0.0580) | ||||||
Indiv 02 | −0.8645* | (0.0624) | ||||||
Indiv 26 | −0.7884* | (0.0580) | ||||||
Indiv 51 | 0.1373* | (0.0712) | ||||||
Indiv 54 | 0.3120* | (0.0645) | ||||||
Indiv 24 | 1.1369* | (0.0580) | ||||||
Indiv 28 | 0.2357* | (0.0504) | ||||||
Indiv 33 | −0.1863* | (0.0623) | ||||||
Indiv 42 | −1.1086* | (0.0532) | ||||||
Indiv 44 | 1.4785* | (0.0594) | ||||||
Indiv 50 | −0.6624* | (0.0801) | ||||||
Indiv 08 | 0.2206* | (0.0569) | ||||||
log (nt) | 0.6394* | (0.0118) | 0.3884* | (0.0120) | 4.0946* | (0.0121) | ||
Yt−1 | 0.8946* | (0.1019) | 0.3120* | (0.1042) | 0.2808* | (0.1052) | ||
log (9-cyclet−1 + 1) | 0.0880* | (0.0095) | 0.1077* | (0.0095) | ||||
Monday | −5.9929* | (0.1768) | −12.2986* | (0.1776) | ||||
Tuesday | −4.1357* | (0.1665) | −9.5061* | (0.1643) | ||||
Wednesday | −3.7315* | (0.1225) | −10.6229* | (0.1248) | ||||
Thursday | −4.0714* | (0.1057) | −10.6006* | (0.1108) | ||||
Friday | −4.7021* | (0.1305) | −11.6135* | (0.1308) | ||||
Saturday | −4.2353* | (0.0564) | −11.4279* | (0.0569) | ||||
Sunday | −4.9328* | (0.0837) | −12.5474* | (0.0840) |
Note: The lag term is t − 1. The days of the week stand in for the intercept term in models 3 and 4; indiv k indicates the density effect for individual k (as indexed in the data set); log (nt) indicates the contagious propensity effect and is the log of the network size at time t; again, Yt−1 represents the lag effect and log (9-cyclet−1 + 1) is the embeddedness cycle statistic; and indicates that a given variable is represented via a dummy variable.
p <.05.