CODEWITHSUNDEEP
rregressioncategoriesmultinomialordinal
An116
An116

Reputation: 911

Multinomial regression : how to show all coefficients without L, Q and R?

I have this dataframe that I applied multinom function

df = data.frame(x = c('a','a','b','b','c','c','d','d','d','e','e','f','f',
                      'f','f','g','g','g','h','h','h','h','i','i','j','j'),
                y = c(1,2,1,3,1,2,1,4,5,1,2,2,3,4,5,1,1,2,1,2,2,3,2,2,3,4) )
df$y = factor(df$y,ordered = TRUE)


nnet::multinom(y~x, data = df)

when checking the output, I have all the variables with their coefficients (meaning everything is fine)

Coefficients:
    (Intercept)        xb            xc        xd            xe       xf
2 -6.045294e-05 -31.83512  3.800915e-05 -36.67053  3.800915e-05 25.00515
3 -1.613311e+01  16.13310 -1.725649e+01 -21.06832 -1.725649e+01 41.13825
4 -1.692352e+01 -14.71119 -1.428100e+01  16.92351 -1.428100e+01 41.92865
5 -2.129358e+01 -10.49359 -1.002518e+01  21.29353 -1.002518e+01 46.29867
           xg          xh        xi         xj
2  -0.6931261   0.6932295 40.499799 -25.311410
3 -24.0387863  16.1332150 -8.876562  45.191730
4 -20.2673490 -16.0884760 -6.394423  45.982129
5 -15.1755064 -11.8589447 -4.563793  -6.953942

but my original dataframe (will share only the output) that is coded as the dependent and independent variables from the df dataframe (meaning as ordinal factors) and all the analysis is well done but when it comes to interpretation I have this output :

Coefficients:
  (Intercept)   FIES_R.L    FIES_R.Q   FIES_R.C    FIES_R^4     FIES_R^5
2 -0.09594409  -1.303256  0.03325169 -0.1753022 -0.46026668 -0.282463422
3 -0.18587599  -1.469957  0.42005569 -0.2977628  0.00508412  0.003068678
4 -0.58189239  -2.875183  0.33128994 -0.6787992  0.11145099  0.239368520
5 -2.68727952 -10.178604 -5.12515249 -5.8454920 -3.13775961 -1.820629143
    FIES_R^6   FIES_R^7   FIES_R^8
2 -0.2179067 -0.1000471 -0.1489342
3  0.1915476 -0.5483707 -0.2565626
4  0.2585801  0.3821566 -0.2679774
5 -0.5562958 -0.6335412 -0.7205215

I don't want FIES_R.L,FIES_R.Q and FIES_R.C. I want them as : FIES_R_1, FIES_R_2, FIES_R_3, FIES_R_4, FIES_R_5, FIES_R_6, FIES_R_7, FIES_R_8, why I have such an output ? knowing that the two dataframes include ordinal categorical variables and the x variable and the FIES variable include many categories in both dataframes. Thanks

Upvotes: 1

Views: 242

Answers (2)

Ricardo Semião
Ricardo Semião

Reputation: 4456

You can change the coefnames "by hand":

mod = nnet::multinom(y~x, data = df)
mod$vcoefnames = c("(Intercept)", paste0(substr(mod$vcoefnames, 1, 6), "_", 1:8))

Upvotes: 1

An116
An116

Reputation: 911

I just figured it out : because the independent variable is an ordinal factor. Meaning FIES in my dataset in an ordinal factor. When I used the argument ordered = FALSE the problem got solved

Upvotes: 1

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