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How do I get average marginal effects (AMEs) for each category/threshold in a partial proportional odds model (PPOM)?

This is my first post in this forum. I hope that I have heeded the most essential recommendations for asking good questions.

This sample dataset consists of an ordinal outcome variable (Y1) and three independent variables (VAR1, VAR2, VAR3).

set.seed(3)
sampleData <- data.frame(id = 1:1000, Y1 = sample(c("1", "2", "3", "4"), 
 1000, replace=TRUE), Var1 = rnorm(1000, 40, 10), 
 Var2 = rnorm(1000, 60, 10), Var3 = rnorm(1000, 80, 5))

Assuming proportional odds assumption is violated, one could carry out a partial proportional odds model (PPOM) using package ordinal to predict Y1 by the three independent variables (Var1, Var2, Var3).

library(ordinal) 
PPOM <- clm(as.factor(Y1) ~ Var1 + Var2 + Var3, 
 nominal = ~ Var1 + Var2 + Var3, data = sampleData)

We get the following output with coefficients for each category:

summary(PPOM)

formula: as.factor(Y1) ~ Var1 + Var2 + Var3
nominal: ~Var1 + Var2 + Var3
data: sampleData

 link threshold nobs logLik AIC niter max.grad cond.H 
 logit flexible 1000 -1381.17 2786.34 4(0) 2.82e-10 2.2e+07

Coefficients: (3 not defined because of singularities)
 Estimate Std. Error z value Pr(>|z|)
Var1 NA NA NA NA
Var2 NA NA NA NA
Var3 NA NA NA NA

Threshold coefficients:
 Estimate Std. Error z value
1|2.(Intercept) 0.4952642 1.2260010 0.404
2|3.(Intercept) 1.9790234 1.0724982 1.845
3|4.(Intercept) 2.0892425 1.2550636 1.665
1|2.Var1 0.0026194 0.0075920 0.345
2|3.Var1 -0.0077578 0.0065845 -1.178
3|4.Var1 -0.0064243 0.0075364 -0.852
1|2.Var2 -0.0001089 0.0074568 -0.015
2|3.Var2 -0.0082836 0.0063447 -1.306
3|4.Var2 -0.0073638 0.0071008 -1.037
1|2.Var3 -0.0219767 0.0140701 -1.562
2|3.Var3 -0.0157235 0.0121943 -1.289
3|4.Var3 -0.0047098 0.0141844 -0.332

I am interested in AMEs for each predictor for each category. By using margins I get only AMEs for all of the thresholds together.

library(margins) 
summary(margins(PPOM))

Output:

 factor AME SE z p lower upper
 Var1 0.0000 0.0000 1.1365 0.2557 -0.0000 0.0001
 Var2 0.0000 0.0000 1.3056 0.1917 -0.0000 0.0001
 Var3 0.0001 0.0001 0.9990 0.3178 -0.0001 0.0002

Does anyone know hot to calculate AMEs for each category?

Any help would be greatly appreciated!