customize facet direction in plot.parameters_model

[madebyafox]

Would be LOVELY if users could customize the facet direction (i.e. rows vs columns) in the see plot() functions that render coefficients for multiple equations. (eg. multinomial regressions)

see sample of default in sjPlot (facet column-wise) vs plot(model_parameters) (facet row-wise)
perhaps also worth considering adding option of keeping scale the same across the plots (thus rendering plots with difference sizes)? As seen in this example, vertical visual comparison across parameters here is dangerous due to differences in scale across the row-wise facets

REPREX

library(mclogit)
#> Loading required package: Matrix
library(easystats)
#> Warning: package 'easystats' was built under R version 4.2.3
#> # Attaching packages: easystats 0.6.0.8
#> ✔ bayestestR  0.13.0.10   ✔ correlation 0.8.3.3  
#> ✔ datawizard  0.7.0.5     ✔ effectsize  0.8.3.6  
#> ✔ insight     0.19.1.2    ✔ modelbased  0.8.6.3  
#> ✔ performance 0.10.2.7    ✔ parameters  0.20.2.14
#> ✔ report      0.5.7.1     ✔ see         0.7.5.1
library(sjPlot)

#CREATE MIXED MULTINOMIAL LOGISTIC REGRESSION MODEL
pict  <- base::readRDS(url("https://slcladal.github.io/data/pict.rda", "rb"))
m1.mn <- mblogit(formula = Response ~ Gender + Group,
              random = ~ 1 | Item,
              data = pict)
#> 
#> Iteration 1 - deviance = 1667.891 - criterion = 0.8014916
#> Iteration 2 - deviance = 1576.67 - criterion = 0.08187338
#> Iteration 3 - deviance = 1550.621 - criterion = 0.03072031
#> Iteration 4 - deviance = 1541.316 - criterion = 0.009764653
#> Iteration 5 - deviance = 1537.509 - criterion = 0.002514804
#> Iteration 6 - deviance = 1536.103 - criterion = 0.000306996
#> Iteration 7 - deviance = 1535.722 - criterion = 4.709478e-05
#> Iteration 8 - deviance = 1535.593 - criterion = 7.320379e-06
#> Iteration 9 - deviance = 1535.547 - criterion = 1.195585e-06
#> Iteration 10 - deviance = 1535.529 - criterion = 1.993986e-07
#> Iteration 11 - deviance = 1535.522 - criterion = 3.342435e-08
#> Iteration 12 - deviance = 1535.519 - criterion = 5.601294e-09
#> converged

#SEE 
## stacked 3 rows 
mp <- model_parameters(m1.mn, exponentiate = T)
plot(mp, stack=F)

#SJPLOT
## across 3 columns
plot_model(m1.mn)

^{Created on 2023-03-27 with reprex v2.0.2}

[strengejacke]

You need the n_column argzument: plot(mp, stack=FALSE, n_column = 3)

[strengejacke]

Does this solve your issue?