Journal of the Royal Statistical Society. Series D (The Statistician), Vol. 47, No. 2 (1998), pp. 377-383 (7 pages) In medical and social surveys a large number of multiply correlated explanatory ...
Beside the model, the other input into a regression analysis is some relevant sample data, consisting of the observed values of the dependent and explanatory variables for a sample of members of the ...
The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models ...
Linear regression is a powerful and long-established statistical tool that is commonly used across applied sciences, economics and many other fields. Linear regression considers the relationship ...
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 ...
Time-dependent variables can be used to model the effects of subjects transferring from one treatment group to another. One example of the need for such strategies is the Stanford heart transplant ...
The Canadian Journal of Statistics / La Revue Canadienne de Statistique, Vol. 27, No. 1 (Mar., 1999), pp. 63-79 (17 pages) In some physical systems, where the goal is to describe behaviour over an ...
The application of Cox proportional hazards (CoxPH) models to survival data and the derivation of hazard ratio (HR) are well established. Although nonlinear, tree-based machine learning (ML) models ...
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