Sentence examples for stepwise model reduction from inspiring English sources
No stepwise model reduction was applied because such methods dramatically increase the rate of type I errors [26], and because our aim here was to obtain the most accurate point estimates and their confidence intervals (CI) [27].
In the stepwise model reduction, GRO and SMZ could be joined into one factor level (χ = 0.40, df = 2, P = 0.82), and the combined GRO + SZM trait could be joined with PMN (χ = 3.81, df = 2, P = 0.15).
The optimal fixed structure for ANOVAs, linear mixed-effects models, generalized linear models, and generalized linear mixed-effects models was found by stepwise model simplification and factor level reduction followed by the comparison of the models via the Akaike information criterion (AIC, Akaike, 1973).
The Akaike information criterion (AIC) was applied for metabolite-specific stepwise model evaluation and reduction of model complexity with regards to fixed effects (all fixed effects except time were considered optional).
At the next step, post-baseline values for baseline variables selected by the stepwise procedure were added to the model, and model reduction using stepwise selection was applied.
The use of model reduction (by a stepwise technique) does not improve the R2 of prediction of the two models, respectively equal to 0.89 and 0.92.
Model reduction was performed by stepwise backward elimination, removing variables and interactions not significant at P < 0.05.
Model reduction was carried out using stepwise backwards elimination, removing variables with p > 0.05.
The same two calculations are performed for the stepwise model.
We simulated microsatellite loci following a generalized stepwise model [34] [35].
