Table 2.

Models for analyzing breeding trajectories. ${\mathit{\alpha }}_i^{\ast }$ is an individual univariate random effect because only breeding success was analyzed at this stage

${\mathcal{M}}_{\mathrm{nil}}$	${\text{success}}_{it}\sim \text{Bernoulli}({\text{logit}}^{-1}(\mathit{\mu }))$
${\mathcal{M}}_{\mathrm{NTLH}}$	${\text{success}}_{it}\sim \text{Bernoulli}({\text{logit}}^{-1}(\mathit{\mu }+\mathit{\gamma }\times {\text{success}}_{i(t-1)}))$
${\mathcal{M}}_{\mathrm{HPDH}}$	${\text{success}}_{it}\sim \text{Bernoulli}({\text{logit}}^{-1}(\mathit{\mu }+{\mathit{\alpha }}_i^{\ast }))$
${\mathcal{M}}_{\mathrm{full}}$	${\text{success}}_{it}\sim \text{Bernoulli}({\text{logit}}^{-1}(\mathit{\mu }+\mathit{\gamma }\times {\text{success}}_{i(t-1)}+{\mathit{\alpha }}_i^{\ast }))$