. Author manuscript; available in PMC: 2019 Jun 30.

Published in final edited form as: J Proteome Res. 2018 May 25;17(7):2460–2469. doi: 10.1021/acs.jproteome.8b00224

Table 2.

Summary of each feature used to develop the logistic regression predictive algorithm for prodromal Parkinson’s disease in serum.

	Estimate	Std. Error	z value	Pr(>\|z\|)	Odds
(Intercept)	0.981	0.723	1.357	0.175	-
PC ae C36:4	3.34	4.863	0.687	0.492	28.23
t4-OH-Pro	2.768	1.414	1.958	0.05	15.93
PC ae C38:5	−1.326	4.027	−0.329	0.742	0.27
PC aa C34:2	−1.076	1.306	−0.824	0.41	0.34