Inconsistency Factors' Spike and Slab

The function visualizes the inconsistency factor's effect when the inconsistency factor is included in the Network Meta-Analysis (NMA) model and when is not.

Usage

spike.slab(x)

Arguments

x

An object of class ssifs.

Value

An object of class ggplot.

Details

The function creates two density plots for each inconsistency factor based on the inconsistency factors' effects, which are obtained from the ssifs model. The former visualizes the effect when the inconsistency factor is included in the NMA model (spike), while the latter when is not (slab). A good mixing of the SSIFS model indicates that the spike has high density for values close to zero whereas the slab is flatter.

Examples

data(Alcohol)

TE <- Alcohol$TE
seTE <- Alcohol$seTE
studlab <- Alcohol$studyid
treat1 <- Alcohol$treat2
treat2 <- Alcohol$treat1

# Stochastic Search Inconsistency Factor Selection using intervention AO-CT as reference.
m <- ssifs(TE, seTE, treat1, treat2, studlab, ref = "AO-CT",
M = 500, B = 100, M_pilot = 300, B_pilot = 100)
spike.slab(m)
#> $`BASICS ; Alc101_BASICSAlc101`

#> 
#> $`Alc101 ; AO-CT_Alc101AO-CT`

#> 
#> $`BASICS ; e-CHUG_BASICSe-CHUG`

#> 
#> $`THRIVE ; Active-CT_THRIVEActive-CT`

#> 
#> $`e-CHUG ; AO-CT_e-CHUGAlcEduAO-CT`

#> 
#> $`AlcEdu ; AO-CT_e-CHUGAlcEduAO-CT`

#> 
#> $`e-CHUG ; AO-CT_e-CHUGBASICSAO-CT`

#> 
#> $`BASICS ; AO-CT_e-CHUGBASICSAO-CT`

#> 
#> $`AlcEdu ; AO-CT_Alc101AlcEduAO-CT`

#> 
#> $`Alc101 ; AO-CT_Alc101AlcEduAO-CT`

#>