finalLRModel: Method "finalLRModel"
In PhenStat: Statistical analysis of phenotypic data

Description Usage Arguments Value Author(s) References See Also Examples

This is an internal function run within LR framework. It completes the final stage of the LR framework, which builds the final model and estimates effects. As an internal function, it doesn't include extensive error testing of inputs. Please use cautiously if calling directly.

Works with PhenTestResult object created by startLRModel function. The creation of LR final model is based on the significance of different fixed effects, depVariable and equation values stored in PhenTestResult object.

1 2	finalLRModel(phenTestResult, outputMessages = TRUE)

`phenTestResult`	instance of the `PhenTestResult` class that comes from the function `testDataset`; mandatory argument
`outputMessages`	flag: "FALSE" value to suppress output messages; "TRUE" value to show output messages; default value TRUE

Returns results stored in instance of the PhenTestResult class

Natalja Kurbatova, Natasha Karp, Jeremy Mason

Karp N, Melvin D, Sanger Mouse Genetics Project, Mott R (2012): Robust and Sensitive Analysis of Mouse Knockout Phenotypes. PLoS ONE 7(12): e52410. doi:10.1371/journal.pone.0052410

West B, Welch K, Galecki A (2007): Linear Mixed Models: A practical guide using statistical software New York: Chapman & Hall/CRC 353 p.

PhenTestResult and testDataset

    file <- system.file("extdata", "testLR.csv", package="PhenStat")
    testLR <- PhenStat:::PhenList(dataset=read.csv(file,na.strings = '-'),
            testGenotype="Mock")
    testLR2 <- PhenStat:::LRDataset(testLR,"V2")
    
    # when "testDataset" function's argument "callAll" is set to FALSE 
    # only "startLRModel" function is called - the first step of LR framework
    resultLR <- PhenStat:::testDataset(testLR2,
            depVariable="V2",
            callAll=FALSE,
            method="LR")
    # print out formula that has been created
    PhenStat:::analysisResults(resultLR)$model.formula.genotype
    # print out batch effect's significance 
    PhenStat:::analysisResults(resultLR)$model.effect.batch
    resultLR <- PhenStat:::finalLRModel(resultLR)