I am getting astronomically high p-values for all the coefficients in a logistic regression model. I am not sure why they are so high:
I honestly cannot find out why they are so high. My dependent variable consists of ratios between 0 and 1, and my independent variables vary between continuous data, ordinal data, and categorical data.
Just adding a bit more information. I am creating a model to 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 where each hour before effects the value of each hour after it. In the literature they call it the sequential logit model. Currently I am using Matlab's generalized linear model function using a binomial distribution linked with a logit. I am using 9 independent (predictor) variables and one dependent variable that is continuous between 0 and 1.
More information! The model being developed operates only on people that have already made the decision to evacuate. So I am not testing for if they will leave or not but when they will leave. Hopefully this clarifies what I am trying to do.
I downloaded R and I ran a logistic test. Here is what I got
Deviance Residuals: Min 1Q Median 3Q Max -0.41146 -0.12817 -0.00301 0.10222 0.47937 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -36.87241 570.55243 -0.065 0.948 Hour -0.27353 1.00636 -0.272 0.786 LN.TU. -3.96075 8.57513 -0.462 0.644 as.factor(Evac1)1 3.34697 13.38238 0.250 0.803 as.factor(Evac2)1 1.42544 3.51690 0.405 0.685 Pressure 0.04122 0.59701 0.069 0.945 WindSpeed -0.01583 0.23526 -0.067 0.946 as.factor(Time1)1 10.11888 11.22222 0.902 0.367 as.factor(Time2)1 9.89199 10.45510 0.946 0.344 as.factor(Time3)1 10.72968 9.48993 1.131 0.258 (Dispersion parameter for binomial family taken to be 1) Null deviance: 14.5671 on 36 degrees of freedom Residual deviance: 1.5175 on 27 degrees of freedom AIC: 27.927 Number of Fisher Scoring iterations: 9
My p-values remain very unappealing. I am beginning to think that instead of trying to fix this, I should just believe that what I am doing is wrong and take another approach. Thanks all who answered and helped!