Sentence examples for models with p from inspiring English sources

Stepwise unconditional multivariable logistic regression was used to develop prediction models with p = 0.01 used to enter and remain in the model.

Differences between models with P values <0.05 were considered significant.

The combined odds ratio (OR) was estimated using fixed effects (FE) models with p heterogenity  ≥ 0.10, or random-effects (RE) models with p heterogenity  < 0.10 [ 28].

Ba ckwards stepwise regression models with p > 0.2 for removal from model.

The models with P < 0.05 represent rejection of the models and they are indicated in boldface.

They demonstrated that this approach works well when fitting regression models with p ≫ n data.

To account for non-linear relationships, we apply non-parametric survival models with P-splines.

Our proposal consists of categorising continuous variables by using GAM models with P-spline smoothers.

All genes that fitted to one of those 8 models with p-value lower than 0.01 were considered age-related genes.

Crude models [see Supplemental Material (doi 10.1289/ehp.0901182)] were generally consistent with the adjusted models, with p-values in some cases being slightly lower in the crude models.

We defined significant SigB binding sites as DNA regions that aligned to both the SigB HMM and PWM models, with p-values equal to or below at least one of their respective p-value cut-offs.