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Minimal adequate models were obtained by stepwise elimination of nonsignificant terms (Crawley 2007).
Minimal adequate models were obtained by backward stepwise elimination (i.e. sequentially dropping the least significant terms from the full model, until all terms in the model were significant).
We used both backward and forward stepwise model simplification, based on AIC to find a minimal adequate model for each response, using the function stepAIC (MASS package73).
In Coleman v. Brown, filed in 1990, the District Court found that prisoners with serious mental illness do not receive minimal, adequate care.
In the minimal adequate analysis of covariance (ANCOVA) model (Table 2), the only statistically significant effects on log variance were due to log mean, to treatment, and to treatment × log mean interaction, indicating differences in slope among treatments.
The minimal adequate model was selected as the one containing nothing but significant variables.
Although per-capita GDP was retained in our minimal adequate model, two points are worth mentioning.
The numerical output of the minimal adequate model was obtained using REML estimation [42].
The numerical output of the minimal adequate model was obtained using REML estimation (Appendix S1) [42].
For each response variable (ecosystem process), we performed multiple regressions and we then selected the minimal adequate model.
We used backward selection to obtain the minimal adequate model with a selection criterion of α = 0.05.
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