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I am creating a model that predicts the availability of machines. Historical data is given as a percentage of time that the machine is available. (e.g. machine x was available 95% of the time)
I would thus compute a logit specification model with the dependant variable not being 0 or 1, but within the interval (0,1). Is it valid and possible to use logistic regression on this scenario?
The answer depends on what exactly is your data. If your data are sample sizes $n_i$ and observed proportions of success $p_i$, then you can use logistic regression to model such data. On another hand, if you only have values in $(0, 1)$ that you want to model, then this kind of data is to be modeled with beta regression, a regression model for conditional distribution that is bounded on both sides, modeled using beta distribution parametrized by mean and precision.
