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. 2017 Jun 15;7(15):5580–5591. doi: 10.1002/ece3.3082

Table 2.

Predictor weights calculated as the sum of the Akaike weights for each mixed‐effects logistic regression explaining variation in probability of giving birth to a foal surviving to late summer (n horse = 113, n observations = 496) or probability of weaning a foal (survival to year t + 1; n horse = 113, n observations = 321) in which that variable appeared

Predictor Analysis
Probability of giving birth Probability of weaning
Repro t − 1 1.00 0.93
Female quality 0.95 1.00
Female age² 0.96 1.00
Location 0.00 0.01
Density 1.00 0.98
Band size 1.00 0.94
Local sex ratio 0.45 0.43
Band sex ratio 0.97 0.80
Winter severity t − 1 0.55
Winter severity 0.82 0.67
Winter severity t + 1 1.00
Female quality: Repro t − 1 0.73 0.58
Female age²: Repro t − 1 0.92 0.19
Location: Repro t − 1 0.00 0.00
Density: Repro t − 1 0.43 0.28
Band size: Repro t − 1 0.37 0.27
Local sex ratio: Repro t − 1 0.12 0.21
Band sex ratio: Repro t − 1 0.38 0.37
Winter severity t − 1: Repro t − 1 0.14
Winter severity: Repro t − 1 0.22 0.17

Models included a combination of the following factors: female quality, female age, location on the island, local density, band size, band sex ratio, winter severity, and their interaction with reproductive status as fixed effects and horse identity as a random factor. Variables retained in the selected model are in bold.