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We tested the significance of model terms by performing F tests on models fit with and without the term of interest.
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Ledalab uses two approaches to invert the peripheral model, termed by the authors "Discrete Deconvolution Analysis" (DDA) (Benedek & Kaernbach, 2010b) and "Continuous Deconvolution Analysis" (CDA) (Benedek & Kaernbach, 2010a).
The SMSS compares the linear, two-factor interaction (2FI), quadratic and cubic models by using the statistical significance of adding new model terms, step by step in increasing order [35].
The effects of separate parameters and interactions were analyzed by analysis of variance and the equation and model terms were analyzed by Fisher's test for model significance.
Model terms were evaluated by the P value.
Model terms were evaluated by the P value (probability) with 95%% confidence level.
The significance of the model equation and model terms was evaluated by F test (Jadhav et al. 2013).
Model terms were selected by backwards stepwise reduction to minimize AIC.
Then the effects of current dose are captured by model terms γ1(1), γ1(2), and γ1(3).
Further this modified model, termed CARE by Gail et al[ 8], is more parsimonious in that age-at-birth of first live child and its interaction with the number of affected first-degree-relatives are no longer included.
We fitted 'salinity concentration', 'habitat', 'location' and 'species' as fixed effects in the GLMMs; the random effects were 'salinity concentration' included as a linear model term grouped by 'locality' and 'breeding site', with 'breeding site' nested within 'locality'locality
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