An introduction to the programming language R for environmental researchers

In the following some results of multiple linear regression models are presented, where couplings between climate variables and fish stock variables have been used to model

In the following some results of multiple linear regression models are presented, where couplings between climate variables and fish stock variables have been used to model

linear mixed effects models (e. g., logistic regression with random intercepts and

Section 6 uses two examples to compare the prediction performances between the proposed ATRP model and some existing models (including linear regression with time series errors

The estimates then indicate the marginal effect of increasing family size by 1 child (e.g. from 1 child family with 0 siblings to a 2 child family with 1 sibling) or being 1

We fitted multivariable models, using generalized linear (here both logistic and linear) regression, weighted quantile sum (WQS) regression, and Bayesian kernel machine

Results of ExWAS (i.e., exposure by exposure linear regression models) and ExWAS-MLR (i.e., multiple linear regression model simultaneously including all exposures selected in

Multivariate ANOVA (SPSS, Generalized Linear Models (GLM), Generalized Estimating Equations (GEE)) was.. conducted to investigate the impact of parental alcohol abuse on the