I'm trying to fit a glm in R
My code is the following:
glm(formula = DV ~ IV1between*IV2within, data = df).
The DV distribution (not the residual!) is approximately an ex-gaussian.
Which "family" argument should I use?
Any tips are welcome, thanks!
What is the type of variable that describes the DV? BTW.. what is ex-gaussian? David Booth
Thank you for your reaction David.
The DV consists of a continuous variable. Its values could range from 0 to 100. Given a statement, participants had to answer using a VAS scale ranging from 0 = “strongly disagree” to 50 = “neither agree nor disagree” to 100 = “strongly agree”.
About the ex-gaussian distribution (citing the paper by Parris et al., 2013, Frontiers in Psychology): "the ex-Gaussian distribution is a mathematical convolution of the normal (Gaussian) and exponential distributions and has three parameters which are μ (mu) and σ (sigma), reflecting the mean and standard deviation of the Gaussian distribution, and τ (tau), reflecting the mean and standard deviation of the exponential distribution. Intuitively, distribution shifting is reflected in μ, and distribution skewing is reflected in τ"
The best I can do is to point you to the attached screenshot of a paper that I think you should read. Best wishes David Booth
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