fitLMEModel: A function to fit a linear mixed effects (LME) model of...

In SPreFuGED: Selecting a Predictive Function for a Given Gene Expression Data

Description

This function fits a LME model to the log-odds of accuracy (for binary direct classifiers), logit transformation of the transformed Brier Score (for binary probabilistic classifiers) or logit transformation of the transformed integrated Brier score (for survival data).

Usage

fitLMEModel(type="Accuracy")

Arguments

type	takes Accuracy (Default), for direct classifiers or Probability, for probabilistic classifiers or Survival, for survival predictions.

Details

Depending of the value of type, this function uses either avAcc, avBS or avSurv data to build a LME model. Only the avAcc is available and hence LME model of log-odds accuracy is possible at the moment.

Value

A list containing:

model	an object of class "lmer" for which several fucntions can be applied
type	the type of predictions (Accuracy, Probability or Survival)
fitData	fitted data, contains the variables and their standardized values

Author(s)

Victor Lih Jong

References

Jong VL, Novianti PW, Roes KCB & Eijkemans MJC. Selecting a classification function for class prediction with gene expression data. Bioinformatics (2016) 32(12): 1814-1822

See Also

estimateDataCha, SPreFu and plotSPreFu

Examples

myFit<-fitLMEModel();  #Takes roughly 250 Sec

SPreFuGED documentation built on May 2, 2019, 9:40 a.m.