MixedModelDiag: Model Diagnosis

In usplos/YawMMF: Effective functions for Generalized Mixed Model

Model Diagnosis

Description

To provide more comprehensive and objective information for the model based on the parameter

Usage

MixedModelDiag(data, DV, IV, randomfactor, randomeffect, PCAdeletecriterion = 0, Family = 'gaussian')

Arguments

data	The data that contains the variables in the model
DV	Dependent vairable name. A character parameter
IV	The fixed effect. A character parameter, like 'A + B', or 'A*B'
randomfactor	The name of random factor. A character parameter. If you have more than one factors, input them as a string, collapsed by comma, like 'subj, item'
randomeffect	The name of random intercept and random slope. A character parameter. For example, if you want add intercept and random slope of factor 'CondA', set it '1+CondA'. If you have more than one random factor, input the random effects as a string, collapsed by comma, like '1+CondA, 1+CondA'. Be sure that the order of random effects and that of random factor are same.
PCAdeletecriterion	Criteria for determining whether to remove the component in the random effects. Default value is 0
Family	The distribution family of DV. Default is gaussian, that is, normal distribution.

Examples

## Example :
data = DemoData 
        Simplecoding(data = ., Factor = 'CondA,CondB') 
        MixedModelDummy(data = ., Fix_Factor = 'CondA,CondB',MatrixDesign = '*',ContrastsM = F)
MixedModelDiag(data = data,
               DV = 'DV',
               IV = 'CondA*CondB',
               randomfactor = 'subj,item',
               randomeffect = '1+CondA1+CondB1+CondA1_CondB1,1+CondA1+CondB1+CondA1_CondB1',
               PCAdeletecriterion = 0)

usplos/YawMMF documentation built on July 12, 2024, 1:35 a.m.