Значения термина generalize additive на английском

Binary logistic regression analyses and generalized additive models were used to identify associations.

Linear and generalized additive models were used to evaluate linear and non-linear associations.

Generalized additive models investigated interactions with sex, eczema and aeroallergen sensitization in infancy.

We fitted generalized additive and mixed-effects generalized linear models to describe effects predicting SSIs.

Smoothing splines in generalized additive models were used to estimate associations of parental age with ASD.

Generalized Additive Models were applied to the data to model changes of cell population dynamics over time.

Generalized additive modeling was used to determine how long pro-drinking shifts in beliefs persisted after exposure to advertising.

Time-series analysis of counts was performed by means of generalized additive models with log link and Poisson distribution.

Generalized additive modeling revealed a nonlinear relationship between the variables time to diabetes, and maternal age and perinatal outcome.

A generalized additive Poisson regression model with penalized cubic regression splines was fitted to control for time variant covariates.

Generalized additive model and stratified linear mixed-effects model were developed to identify the effects of multiple meteorological factors on local transmission.

For the individual city analysis, generalized additive models extending Poisson regression, using a smoother to control for seasonal patterns, were applied.

Multivariate Cox regression analysis, stratified analysis and generalized additive model were conducted to reveal the correlation between TG and mortality risk.

To assess potential delayed and non-linear effects of AT on suicides, a lag non-linear model was fitted in a generalized additive model.

Validation studies confirmed that, among new observations arising from the same population, generalized additive model estimates predicted outcomes better than the parametric estimates.

The following models were used: Logistic regression, Generalized Additive Model, Projection Pursuit Regression, Linear Discriminant Analysis, Quadratic Discriminant Analysis and Artificial Neural Networks.