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Model simplification leads to a model with generation time and fecundity remaining.
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We did not perform any model simplification and assessed model fit based on χ2-statistics.
Model simplification and LDA parameters estimation.
Model simplification was performed using a backward stepwise algorithm.
Model simplification produced lower AIC scores in all cases.
We used a backward model simplification procedure by first fitting saturated models.
Furthermore, ΔTC was the only term that was retained after model simplification (Table 1).
Model simplification was done in a stepwise procedure and non-significant terms were excluded [33].
These were used to guide model simplification.
Problematically, model simplification tends to disguise the multiple-testing problem.
Model simplification was performed by using Akaike's information criterion.
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