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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?

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  • $\begingroup$ Hi Machine, welcome! Short answer: yes. $\endgroup$ – Jim May 11 '18 at 10:09
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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.

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