How to obtain the p-values ​of a gamlssMX model?

Question

I am working with a dataset that includes a binary target variable (0 or 1). I have built a model with the gamlssMX() function included on the "gamlss.mx" package to explain a continuous target variable as a function of continuous and qualitative features, alongside with the target one. My goal is to find out if this pathway is significant, but when I build the gamlssMX() model, I get an error when applying the summary() function, which returns p-values associated with each of the features in other models, such as the linear model.

If someone can help me I would appreciate it very much.

Thank you very much!

Answer 1

Does your target variable take values Y>=0 ? If so, you could fit a zero-adjusted continuous distribution, for example ZAGA, zero-adjusted gamma distribution ZAIG, zero-adjusted inverse Gaussian distribution.

The gamlss.inf package in R (for gamlss.inflated) also allows any gamlss continuous distribution for Y>0 to be adjusted to have a point probability at zero.

See Chapter 9 (p177-187) of the book Rigby et al.(2019) ‘Distributions for Modeling Location, Scale, and Shape: Using GAMLSS in R’.

Alternatively you could fit a binary model for Y=0 or not 0, and a continuous distribution for Y>0.

To test the significance of an explanatory variable, it is better (more reliable) to use a generalised likelihood ratio test:

[i.e. compare the difference in global deviance when removing the explanatory variable from the model, against a Chi-squared distribution with the difference in degrees of freedom, (rather than using Wald tests from the summary() output, which are less reliable)].