CaseBasedReasoning (version 0.3)

CoxModel: Cox-Beta Model for Case-Based-Reasoning

Description

Cox-Beta Model for Case-Based-Reasoning

Cox-Beta Model for Case-Based-Reasoning

Super classes

CaseBasedReasoning::CBRBase -> CaseBasedReasoning::RegressionModel -> CoxModel

Public fields

model

the statistical model

model_params

rms arguments

Methods

Public methods

• CoxModel$check_ph()

• CoxModel$clone()

Inherited methods

• CaseBasedReasoning::CBRBase$calc_distance_matrix()
• CaseBasedReasoning::CBRBase$get_similar_cases()
• CaseBasedReasoning::CBRBase$initialize()
• CaseBasedReasoning::RegressionModel$fit()
• CaseBasedReasoning::RegressionModel$print()
• CaseBasedReasoning::RegressionModel$variable_selection()

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Method check_ph()

Check proportional hazard assumption graphically

Usage

CoxModel$check_ph()

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Method clone()

The objects of this class are cloneable with this method.

Usage

CoxModel$clone(deep = FALSE)

Arguments

deep

Whether to make a deep clone.

Details

Regression beta coefficients obtained from a CPH regression model fitted on the training data are used for building a weighted distance measure between train and test data. Afterwards, we will use these weights for calculating a (n x m)-distance matrix, where n is the number of observations in the training data, and m is the number of observations of the test data. The user can use this distance matrix for further cluster analysis or for extracting for each test observation k (= 1,...,l) similar cases from the train data. We use the rms-package for model fitting, variable selection, and checking model assumptions. If the user omits the test data, this functions returns a n x n-distance matrix.