I am trying to work out what precisely this means. Does the points being tightly packed around the middle of the curve just mean that my model isn't that good? Here is my GLM call:
logitmodel=(glm(status~mhi+mgr+edu,data=Rust_Data_10_13,family = binomial)), the summary looks like this:
glm(formula = status ~ mhi + mgr + edu, family = binomial, data = Rust_Data_10_13) Deviance Residuals: Min 1Q Median 3Q Max -1.2804 -0.7331 -0.6343 -0.5115 2.0189 Coefficients: Estimate Std. Error z value Pr(>|z|) (Intercept) -2.072e+00 3.733e-01 -5.551 2.84e-08 *** mhi -8.225e-06 7.425e-06 -1.108 0.26797 mgr 6.808e-04 5.401e-04 1.260 0.20749 edu 2.646e+00 8.689e-01 3.045 0.00233 ** --- Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1) Null deviance: 398.17 on 355 degrees of freedom Residual deviance: 381.21 on 352 degrees of freedom (4 observations deleted due to missingness) AIC: 389.21 Number of Fisher Scoring iterations: 4
and the model that is being graphed here is:
logit_edu<-glm(status~edu, data=Rust_Data_10_13, family= binomial)
I have also graphed a zoomed in version of the model but you cannot see the ends of the curve.
Can anyone help explain why this is happening/is my model just bad?