We demonstrate the feasibility of constructing, interpreting and fitting computable log-linear models to categorical survey data with arbitrary non-nested patterns of non-ignorable non-response. Under ...

We allow the primary response, conditional on the random parameter, to follow a generalized linear model and approximate the generalized linear model by conditioning on the data that describes ...

Keywords: statistical model selection, assumptions, linear regression, ANOVA, machine learning, homoscedasticity, normality, independence, data transformation, non-parametric tests, robust ...

Model building via linear regression models. Method of least squares, theory and practice. Checking for adequacy of a model, examination of residuals, checking outliers. Practical hand on experience ...

The standard linear regression model does not apply when the effect of one explanatory variable on the dependent variable depends on the value of another explanatory variable. In this case, the ...

Traditional statistical models usually conduct a complete case analysis 24 by removing all missing data, which will cause a lack of valid data in areas without air pollution monitoring stations.