. 2016 Jul 11;113(32):8975–8980. doi: 10.1073/pnas.1603431113

Table S1.

Candidate binomial survival models and resultant DIC differences relative to the best model (i.e., model K)

Model	Missing parameters	Formulation (S_i,j)	ΔDIC
A	Linear senescence	$S_{i, t} = β_{0} + β_{1} t^{2} - β_{2, x, s} \sum (e^{- β_{3, x, s} Δ T_{i, t}}) + u_{i}$	479.75
B	Quadratic senescence	$S_{i, t} = β_{0} + β_{1} t - β_{2, x, s} \sum (e^{- β_{3, x, s} Δ T_{i, t}}) + u_{i}$	27.33
C	Replicate	$S_{i, t} = β_{0} + β_{1} t^{2} - β_{2, x, s} \sum (e^{- β_{3, x, s} Δ T_{i, t}})$	485.12
D	Quadratic senescence and replicate	$S_{i, t} = β_{0} + β_{1} t - β_{2, x, s} \sum (e^{- β_{3, x, s} Δ T_{i, t}})$	314.62
E	Linear senescence and delayed effect	$S_{i, t} = β_{0} + β_{1} t^{2} - β_{2, x, s} + u_{i}$	863.56
F	Linear senescence, delayed effect and replicate	$S_{i, t} = β_{0} + β_{1} t^{2} - β_{2, x, s}$	1117.6
G	Quadratic senescence and delayed effect	$S_{i, t} = β_{0} + β_{1} t - β_{2, x, s} + u_{i}$	535.75
H	Quadratic senescence, delayed effect and replicate	$S_{i, t} = β_{0} + β_{1} t - β_{2, x, s}$	883.83
I	Senescence and replicate	$S_{i, t} = β_{0} - β_{2, x, s} \sum (e^{- β_{3, x, s} Δ T_{i, t}})$	639.25
J	Senescence	$S_{i, t} = β_{0} - β_{2, x, s} \sum (e^{- β_{3, x, s} Δ T_{i, t}}) + u_{i}$	477.45
K	Full model	$S_{i, t} = β_{0} + β_{1} t + β_{2} t^{2} - β_{3, x, s} \sum (e^{- β_{4, x, s} Δ T_{i, t}}) + u_{i}$	0