Truncation is a well-known phenomenon that may be present in observational studies of time-to-event data. While many methods exist to adjust for either left or right truncation, there are very few ...

Let y = βT x + ∈ denote the intrinsic relation between the response y and a covariate vector x, where ∈ represents an unobservable random variable. A truncated regression model assumes the existence ...

Doubly truncated data arise when the variable of interest is observable only if it falls between pre‐specified lower and upper bounds. This phenomenon poses significant challenges to statistical ...

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The estimation of empirical models is essential to public policy analysis and social science research. Ordinary Least Squares (OLS) regression analysis is the most frequently used empirical model, and ...

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 ...

As the coronavirus disease 2019 (COVID-19) pandemic has spread across the world, vast amounts of bioinformatics data have been created and analyzed, and logistic regression models have been key to ...