Table 1. Logistic regression model for probability of detecting at least one orang-utan on an expedition.
Estimate | Std. Error | z value | Pr(>|z|) | |
Intercept Model 1a | 18.41009 | 16.85967 | 1.092 | 0.27485 |
Intercept Model 1b | 26.636752 | 17.933663 | 1.485 | 0.13747 |
Year Model 1a | −0.01174 | 0.00852 | −1.378 | 0.16820 |
Year Model 1b | −0.015438 | 0.009071 | −1.702 | 0.08879 |
Person Model 1a | 0.02789 | 0.06676 | 0.418 | 0.67605 |
Person Model 1b | −0.164621 | 0.125249 | −1.314 | 0.18873 |
log(Days) Model 1a | 1.92088 | 0.63607 | 3.020 | 0.00253 ** |
log(Days) Model 1b | 1.965192 | 0.639650 | 3.072 | 0.00212 ** |
Model 1a includes the 33 person expedition. Model 1b excludes 33 person expedition. Year = year in which expedition was conducted. Person = number of people on an expedition. Log(Days) = natural logarithm of duration of expedition in days. Significance code: ‘**’: p<0.01.