modelGoudermanLongitudinal: Fitting the Gouderman LME Model with using Gouderman-Data...

In LoBrA: Generalized Spline Mixed Effect Models for Longitudinal Breath Data

Fitting the Gouderman LME Model with using Gouderman-Data Arrangement.

Description

Uses the linear mixed effects modeling to build the final 'Gauderman' model. The 'Gauderman' modification enables the exact calculation of the significance of a specified section of the spline model.

Usage

modelGoudermanLongitudinal(mygaudermanLDO, correctionMethod = "bonferroni")

Arguments

mygaudermanLDO	GaudermanLDO data object, created by the generalized 'Gauderman' algorithm (GGA).
correctionMethod	correction for p-values. Possible methods: 'holm', 'hochberg', 'hommel', 'bonferroni', 'BH', 'BY', 'fdr', 'none'

Value

'GaudermanModelEvaluation' Results of the evaluation of the Fitted linear mixed effect models for the defined time periods.

Examples

  
  data(LoBraExample)
  selectedLDO <- selectComponents(ldo, components)
  gaudermanLDOexample <- createGoudermanData(selectedLDO, breaks=c(8, 12), center=12, timeperiod=2)
  evalResult<- modelGoudermanLongitudinal(gaudermanLDOexample)
  message(evalResult@correctedpvalues<0.005)
  

LoBrA documentation built on March 22, 2022, 1:06 a.m.