*Bounty: 50*

*Bounty: 50*

I used a gamlss model for my data and would like to do some post hoc analysis afterwards. I tried the packages emmeans and ggemmeans but both of them give me an error: "Error in match.arg(type) : ‘arg’ should be one of “link”, “response”, “terms”"

Here is the code:

```
library(gamlss)
model1 <- gamlss(y ~ x1 + x2 + x3, data=na.omit(Dataset), family=ZAGA)
library(ggemmeans)
ggemmeans(model1, terms = "x1")
```

results in

```
Can't compute marginal effects, 'emmeans::emmeans()' returned an error.
Reason: 'arg' should be one of “link”, “response”, “terms”
You may try 'ggpredict()' or 'ggeffect()'.
```

and

```
library(emmeans)
emmeans(model1, "x1")
```

results in

```
[15] ERROR:
'arg' should be one of “link”, “response”, “terms”
```

From this question I get that this may have nothing to do with the packages but with the way my data is organized. However the solution to the question in the linked post (using ggemmeans instead of emmeans) does not work for me.

Can anyone help me to understand how I should structure my data in order to do a post hoc analysis for a gamlss model in R? Any other suggestion on how to do a posthoc test on this model is very welcome.

Here is my data:

```
x1,x2,x3,y
a,K1,6696,0
a,K6,274,0
a,K3,10605,0
a,K5,90,0
a,K2,4986,0
a,K4,4999,0
a,K6,878,0
a,K3,3426,0
a,K3,718,0
a,K4,6445,0
a,K2,3778,0
a,K5,7601,0
a,K2,3041,0
a,K4,6808,0
a,K4,3601,0
a,K2,2646,0
a,K4,3938,0
a,K2,5569,0
a,K4,2741,0
a,K5,5886,0
a,K2,6983,0
a,K2,3200,0
a,K3,2643,0
a,K3,737,0
a,K3,11406,0
a,K3,9340,0
a,K1,8322,0
a,K2,714,0
a,K5,7168,0
a,K1,4469,0
a,K4,4381,0
a,K1,9943,0
a,K5,8066,0
a,K3,9696,0
a,K2,3058,0
a,K6,1038,0
a,K6,1014,0
a,K1,1866,0
a,K6,7696,0
a,K5,2056,0
a,K2,7339,0
a,K2,7339,0
a,K6,6860,0
a,K4,4720,0
a,K2,4726,0
a,K5,2700,0
a,K5,3587,0
a,K5,4880,0
a,K3,4190,0
a,K5,9836,0
a,K5,7728,0
a,K3,4880,0
a,K6,4080,0
a,K1,774,0
a,K6,671,0
a,K6,4200,0
a,K2,3221,0
a,K6,3836,0
a,K4,5919,0
a,K4,5006,0
a,K3,4254,0
a,K6,4400,0
a,K4,9829,0
a,K3,3162,0
a,K2,2410,0
a,K5,44946,0
a,K5,3662,0
a,K1,5124,0
a,K2,5348,0
a,K6,15103,0
a,K6,9783,0.04
a,K4,2439,0.05
a,K5,2068,0.05
a,K3,3015,0.05
a,K5,2885,0.05
a,K6,19781,0.05
a,K3,2164,0.054298642533937
a,K6,10865,0.054545454545455
a,K3,11297,0.066666666666667
a,K6,4080,0.066666666666667
a,K2,1567,0.083333333333333
a,K5,2523,0.1
a,K4,5683,0.1
a,K6,545,0.1
a,K4,5666,0.1
a,K4,1198,0.1
a,K4,45903,0.1
a,K5,20303,0.1
a,K6,6645,0.1
a,K6,200,0.1
a,K6,299,0.1
a,K4,6255,0.1
a,K5,6165,0.1
a,K4,5000,0.1
a,K6,11440,0.1
a,K3,112,0.117647058823529
a,K3,11586,0.142857142857143
a,K6,4367,0.15
a,K6,2349,0.15
a,K5,9818,0.193548387096774
a,K2,1620,0.2
a,K5,15600,0.2
a,K3,5928,0.2
a,K6,547,0.2
a,K3,3584,0.2
a,K4,4545,0.2
a,K3,13904,0.214285714285714
a,K6,5681,0.25
a,K4,23824,0.25
a,K4,2560,0.25
a,K4,9,0.25
a,K2,6970,0.25
a,K3,6607,0.266666666666667
a,K3,1797,0.3
a,K4,831,0.3
a,K3,7532,0.3
a,K2,1695,0.3
a,K2,4482,0.3
a,K2,2953,0.4
a,K3,10053,0.444444444444444
a,K6,22121,0.45
a,K3,7062,0.5
a,K6,8406,0.5
a,K6,18044,0.5
a,K2,6650,0.5
a,K6,7675,0.5
a,K2,3215,0.529100529100529
a,K3,7134,0.533333333333333
a,K3,23513,0.588235294117647
a,K3,4212,0.615384615384615
a,K2,10883,0.666666666666667
a,K1,6412,0.666666666666667
a,K1,1949,0.666666666666667
a,K2,6575,0.666666666666667
a,K2,1068,0.8
a,K4,9921,1
a,K1,10499,1.33333333333333
a,K1,1990,1.33333333333333
a,K2,3253,2
a,K2,22,2.14285714285714
a,K1,13763,3
b,K2,3784,0
b,K1,501,0
b,K3,6624,0
b,K4,474,0
b,K2,837,0
b,K2,1876,0
b,K5,2762,0
b,K4,39269,0
b,K1,1205,0
b,K2,4995,0
b,K2,5299,0
b,K2,304,0
b,K3,293,0
b,K6,7.65075785824725,0
b,K3,3822,0
b,K2,4794,0
b,K2,21065,0
b,K2,5958,0
b,K4,5157,0
b,K6,7544,0
b,K6,4492,0
b,K2,1614,0
b,K4,1062,0
b,K1,431,0
b,K3,575,0
b,K2,1223,0
b,K3,3664,0
b,K6,234,0
b,K2,6437,0
b,K2,6059,0
b,K3,2311,0
b,K3,5279,0
b,K1,4258,0
b,K3,4004,0
b,K6,3939,0
b,K4,4478,0
b,K1,4311,0
b,K6,9054,0
b,K6,1302,0
b,K5,3708,0
b,K3,6435,0
b,K2,1485,0
b,K4,2314,0
b,K6,6026,0
b,K3,3291,0
b,K6,623,0
b,K1,691,0
b,K3,22614,0
b,K1,6922,0
b,K4,4623,0
b,K2,12253,0
b,K4,304,0
b,K3,9245,0
b,K2,35,0
b,K6,160,0
b,K2,6163,0
b,K2,6040,0
b,K2,279,0
b,K3,5425,0
b,K1,7036,0
b,K1,10872,0
b,K3,34,0.025
b,K6,4018,0.045454545454546
b,K3,6601,0.049180327868853
b,K5,831,0.05
b,K5,2175,0.05
b,K5,10854,0.05
b,K4,5016,0.05
b,K4,1911,0.05
b,K3,7444,0.0625
b,K4,1995,0.085714285714286
b,K6,240,0.092307692307692
b,K4,5127,0.1
b,K6,4489,0.1
b,K6,2615,0.1
b,K3,6263,0.111111111111111
b,K3,17412,0.111111111111111
b,K6,5573,0.12
b,K3,2198,0.133333333333333
b,K2,8877,0.142857142857143
b,K5,3878,0.15
b,K3,8698,0.15
b,K6,2213,0.15
b,K3,3852,0.157894736842105
b,K5,3917,0.16
b,K6,0,0.162162162162162
b,K3,9006,0.166666666666667
b,K3,0,0.181818181818182
b,K6,1244,0.2
b,K5,7898,0.2
b,K5,2645,0.2
b,K4,27566,0.2
b,K6,11435,0.2
b,K4,34,0.2
b,K2,5668,0.25
b,K2,900,0.285714285714286
b,K3,1586,0.3
b,K6,620,0.3
b,K2,11576,0.333333333333333
b,K6,2315,0.35
b,K2,3076,0.4
b,K5,916,0.4
b,K6,13595,0.4
b,K6,0,0.4
b,K6,7675,0.4
b,K3,2311,0.4
b,K4,9288,0.4
b,K4,2664,0.428571428571429
b,K3,9413,0.470588235294118
b,K3,1637,0.476190476190476
b,K6,14400,0.5
b,K1,1025,0.5
b,K4,3,0.6
b,K6,2467,0.6
b,K5,1359,0.6
b,K5,916,0.6
b,K2,4.3369083067469,0.666666666666667
b,K1,4947,0.666666666666667
b,K1,10735,0.666666666666667
b,K3,2534,0.666666666666667
b,K2,7912,0.8
b,K2,6040,0.857142857142857
b,K6,5681,0.9
b,K1,1751,1
b,K1,0,1
b,K1,5937,1
b,K3,1797,1.16666666666667
b,K2,2661,1.2
b,K4,11826,1.3
b,K2,10229,1.4
b,K1,3124,2
b,K1,5265,2
b,K2,7720,2.22222222222222
b,K2,20245,2.34375
b,K1,3438,3.11111111111111
b,K5,34318,3.3
b,K1,11290,3.33333333333333
b,K1,1227,3.5
b,K1,5335,3.6
b,K1,1819,8
b,K2,19431,8.25
```