I am having a few problems understanding how logistic regression can be used with a dependent variable that is not binary or dichotomous but instead between proportions of 0 and 1. If any of you can enlighten me that would be wonderful. So far the most I can figure out is that if I were to use a linear regression than the values that I would get would make no sense because they would go above 1 or below 0 but what I do not get and cannot find anyone else doing is using logistic regression to predict how many people are evacuating during a given time interval (in this case 1 hour) and if I can do that. Also for my variables I am using continuous, dichotomous, and ordered kinds of data.
Any and all help is appreciated.
Edited to remove the portion of this question I added to another question.
Also just to give you all a bit more information. I am creating a model that would predict the proportion of those who evacuated to the remaining population in an area. For example, 10 percent evacuated/90 percent left and so on over 37 hours. The data is sequential used where each hour before effects the value of each hour after it. In literature they call it the sequential logit model. Currently I am using matlabs generalized linear model function using a binomial distribution linked with a logit.