bootstrap_parameters and model_parameters provide problematic pd values when specifying type="response" in emmeans function

[InkaMarei]

Hello,
I just wanted to highlight that when speciying type="response" in emmeans when using a generalized linear (mixed) model, the pd values reported by model_parameters() are all 100. When not specifying type="response" the results seem to be correct though.

Here is the example code:

library(glmmTMB)
library(emmeans)
library(parameters)

m2 <- glmmTMB(count ~ spp + mined + (1|site), family=nbinom2, data=Salamanders)

blub <- bootstrap_parameters(m2, test = "pd")

EMM <- emmeans(blub, ~spp, type="response")

model_parameters(contrast(EMM))


EMM <- emmeans(blub, ~spp)

model_parameters(contrast(EMM))

[mattansb]

This is because by default pd is testing for a direction with regard to 0. You can pass a null=1 argument when the estimate is a ratio (or a ratio factor):

library(glmmTMB)
library(emmeans)
library(parameters)

m2 <- glmmTMB(count ~ spp + mined + (1|site), family=nbinom2, data=Salamanders)
blub <- bootstrap_parameters(m2, test = "pd", iterations = 20)

EMM <- emmeans(blub, ~spp, type="response")
model_parameters(contrast(EMM), null = 1)
#> Parameter      | Median |       95% CI |     pd
#> -----------------------------------------------
#> GP effect      |   1.03 | [0.79, 1.33] | 55.00%
#> PR effect      |   0.27 | [0.22, 0.40] |   100%
#> DM effect      |   1.42 | [1.01, 1.80] | 95.00%
#> (EC-A) effect  |   0.46 | [0.37, 0.65] |   100%
#> (EC-L) effect  |   1.78 | [1.52, 2.11] |   100%
#> (DES-L) effect |   2.24 | [1.81, 2.84] |   100%
#> DF effect      |   1.41 | [1.12, 1.56] |   100%

EMM <- emmeans(blub, ~spp)
model_parameters(contrast(EMM), null = 0)
#> Parameter      | Median |         95% CI |     pd
#> -------------------------------------------------
#> GP effect      |   0.03 | [-0.23,  0.29] | 55.00%
#> PR effect      |  -1.32 | [-1.53, -0.91] |   100%
#> DM effect      |   0.35 | [ 0.01,  0.59] | 95.00%
#> (EC-A) effect  |  -0.77 | [-1.00, -0.44] |   100%
#> (EC-L) effect  |   0.57 | [ 0.42,  0.75] |   100%
#> (DES-L) effect |   0.81 | [ 0.59,  1.04] |   100%
#> DF effect      |   0.35 | [ 0.11,  0.44] |   100%