Regression effect process

John O’Quigley ()
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John O’Quigley: University College London, Department of Statistical Science

Chapter Chapter 9 in Survival Analysis, 2021, pp 215-259 from Springer

Abstract: Abstract In this chapter we Regression effect processdescribe the regression effect process. This can be established in different ways and provides all of the essential information that we need in order to gain an impression of departures from some null structure, the most common null structure corresponding to an absence of regression effect. Departures in specific directions enable us to make inferences on model assumptions and can suggest, of themselves, richer more plausible models. The regression effect process, in its basic form, is much like a scatterplot for linear regression telling us, before any formal statistical analysis, whether the dependent variable really does seem to depend on the explanatory variable as well as the nature, linear or more complex, of that relationship. Our setting is semi-parametric and the information on the time variable is summarized by its rank within the time observations.

Date: 2021
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DOI: 10.1007/978-3-030-33439-0_9

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