My minimum adequate model is shown below. My independent variables (e.g. One, Five) represent habitat categories for which species have either been designated to (i.e. the assessment found that they occur there) or not (they are considered not to occur there). My dependent variable groups species as climate change threatened or not. So all variables, independent and dependent, are binary (0,1).
My hypothesis question is as follows:
'Do species for which climate change is a known threat show similarities in terms of habitat associations and is one or more predominant habitat evident compared with species that are not threatened by climate change?'
Specific questions I would like to be answered include:
Would calculating an odds ratio be of use to me (considering all my data are binary)?
What sort of statements do the output I have (below)/or recommended additional statistics (e.g. odds ratios) allow me to make?
Deviance Residuals: Min 1Q Median 3Q Max -0.6900 -0.3589 -0.2550 -0.1931 2.8634 Coefficients: Estimate Std.Error z value Pr(>|z|) (Intercept) -2.18672 0.09957 -21.961 < 2e-16 *** One -1.23943 0.13614 -9.104 < 2e-16 *** Five 0.75144 0.17228 4.362 1.29e-05 *** Seven -0.66517 0.34117 -1.950 0.05122 . Fourteen -0.55602 0.17454 -3.186 0.00144 ** Signif. codes: 0 ‘’ 0.001 ‘’ 0.01 ‘’ 0.05 ‘.’ 0.1 ‘ ’ 1 (Dispersion parameter for binomial family taken to be 1).