finalModel {PhenStat} | R Documentation

## Method "finalModel"

### Description

This is an internal function run within MM framework. It completes the final stage of the MM 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 `startModel` function. The creation of MM final model is based on the significance of different fixed effects, depVariable and equation values stored in `PhenTestResult` object.

### Usage

        finalModel(phenTestResult,
    				outputMessages = TRUE,
    				modelWeight = NULL)

### Arguments

`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
`modelWeight` | A vector of positive values for weights mainly used for appliying windowing to the data

### Value

Returns results stored in instance of the `PhenTestResult` class

### Author(s)

Natalja Kurbatova, Natasha Karp, Jeremy Mason

### References

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.

### See Also

`PhenTestResult` and `testDataset`

### Examples

        file <- system.file("extdata", "test1.csv", package="PhenStat")
        test <- PhenStat:::PhenList(dataset=read.csv(file,na.strings = '-'),
                testGenotype="Sparc/Sparc")
        # when "testDataset" function's argument "callAll" is set to FALSE
        # only "startModel" function is called - the first step of MM framework
        result <- PhenStat:::testDataset(test,
                depVariable="Lean.Mass",
                equation="withoutWeight",
                callAll=FALSE)
        # print out formula that has been created
        # result$model.formula.genotype
        # print out batch effect's significance
        # result$model.effect.batch
        # change the model
        # result <- PhenStat:::testDataset(test,
        #        depVariable="Lean.Mass",
        #        equation="withWeight",
        #        callAll=FALSE)
        # print out new formula
        #result$model.formula.genotype
        # run the final model fitting when statisfied with the model
        result <- PhenStat:::finalModel(result)

[Package PhenStat version 2.26.0 Index]