I would like to use the glm() function in R to run a multivariate logistic regression. I have also run bi-variate statistics for each variable but want a test that controls for all variables at once (what I understand the glm function in R does - let me know if I should use a different function). My problem is that I don't know what to report in an academic paper and can't find anything online. There are clear guidelines for reporting other tests (example: t (34.17) = 2.22, p = 0.033) but I don't know what to report for the glm. Here is the output of my glm:
Call:
glm(formula = EPI ~ premed + kg + sim + bup + premed.min + ami.type + breed, family = "binomial", data = df)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.7316 -0.2980 -0.2351 -0.1573 2.9108
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) -1.364678 1.239446 -1.101 0.2709
premedT 1.103479 0.499234 2.210 0.0271 *
kg -0.032467 0.014633 -2.219 0.0265 *
simS 0.193276 0.431850 0.448 0.6545
bupN 0.037000 1.048603 0.035 0.9719
premed.min 0.002211 0.002542 0.870 0.3845
ami.typeCRI -12.604613 781.507743 -0.016 0.9871
ami.typeDRIP -0.226335 0.466006 -0.486 0.6272
breedYorkshireMix -0.852239 0.489624 -1.741 0.0818 .
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
(Dispersion parameter for binomial family taken to be 1)
Null deviance: 272.44 on 938 degrees of freedom
Residual deviance: 255.21 on 930 degrees of freedom
(1 observation deleted due to missingness)
AIC: 273.21
Number of Fisher Scoring iterations: 15
It doesn't help that I cant figure out how I would report a bi-variate logistic regression either (I've seen people report odds ratios, χ2 values etc). I have found out how to get confidence intervals and odds ratios in R if I need those:
> exp(cbind(OR = coef(LM), confint(LM)))
Waiting for profiling to be done...
OR 2.5 % 97.5 %
(Intercept) 2.554629e-01 2.222514e-02 2.873313e+00
premedT 3.014635e+00 1.198440e+00 8.735251e+00
kg 9.680544e-01 9.402870e-01 9.957784e-01
simS 1.213217e+00 5.144926e-01 2.832683e+00
bupN 1.037693e+00 5.650816e-02 5.366901e+00
premed.min 1.002213e+00 9.966528e-01 1.006788e+00
ami.typeCRI 3.356495e-06 9.742338e-102 1.000098e+12
ami.typeDRIP 7.974511e-01 3.090303e-01 1.957706e+00
breedYorkshireMix 4.264589e-01 1.724568e-01 1.213685e+00
There were 36 warnings (use warnings() to see them)
> warnings()
Warning messages:
1: glm.fit: fitted probabilities numerically 0 or 1 occurred
I want to say something like "The results of the multivariate logistic regression indicated that subjects given pre-medication "T" were more likely to have outcome "EPI" than subjects given pre-medication "X" (blah, blah, p = 0.027) and subjects that had lower "kg" were also more likely to have outcome "EPI" than subjects that had higher "kg" (blah, blah, p = 0.0265)."
EDIT: EPI is a binary variable that is assigned 0 or 1