I am having a little trouble with interpreting the output from my model can anyone give a helping hand.

Ok so it is a Generalised Linear Model in RStudio. My outcome variable is either 0 or 1.

Here is the output summary from my final model:

Call:

glm(formula = outcome ~ Location + Size + Proximity + Location:Size +

Location:Sizeroximity, family = binomial(link = probit),

data = shark2, control = glm.control(50))

Deviance Residuals:

Min 1Q Median 3Q Max

-1.5045 -0.6426 -0.4042 0.7594 1.8072

Coefficients:

Estimate Std. Error z value Pr(>|z|)

(Intercept) 21.166 12.298 1.721 0.0852 .

Location2 -12.222 8.318 -1.469 0.1417

Size -34.364 18.093 -1.899 0.0575 .

Proximity -37.200 16.259 -2.288 0.0221 *

Location2:Size 21.437 12.333 1.738 0.0822 .

Location1:Sizeroximity 56.707 23.854 2.377 0.0174 *

Location2:Sizeroximity 55.816 24.854 2.246 0.0247 *

---

Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

(Dispersion parameter for binomial family taken to be 1)

Null deviance: 44.252 on 32 degrees of freedom

Residual deviance: 25.948 on 26 degrees of freedom

AIC: 39.948

Number of Fisher Scoring iterations: 1

and here is a Model summary:

Call: glm(formula = outcome ~ Location + Size + Proximity + Location:Size +

Location:Sizeroximity, family = binomial(link = probit),

data = shark2, control = glm.control(50))

Coefficients:

(Intercept) Location2

21.17 -12.22

Size Proximity

-34.36 -37.20

Location2:Size Location1:Sizeroximity

21.44 56.71

Location2:Sizeroximity

55.82

Degrees of Freedom: 32 Total (i.e. Null); 26 Residual

Null Deviance: 44.25

Residual Deviance: 25.95 AIC: 39.95

Can anyone help me get my head around what I need to understand to make my write up? I can see that some effects and interactions are significant and they make sense but I am not sure what to do next with the output.

thank you for any guidance.

Darren.