Table S2. Linear model for the chances of a paper being accepted.

We used logit regression to estimate the chances of a paper being accepted as a function of whether the Reviewing Editor served as one of the reviewers (Editor_As_Reviewer), the number of unique reviewers, and the number of days between when a paper was published and the first published paper by eLife. The only significant variable is the days since eLife started accepting papers for publication (although the effect on the chances of a paper being accepted is very small).

	coef	std err	z	P>|z|	[95.0% Conf. Int.]
Intercept	0.6080	0.257	2.368	0.018	0.105 1.111
C(Editor_As_Reviewer)[T.True]	0.0822	0.087	0.946	0.344	-0.088 0.252
Publication_Since_Start	-0.0003	0.000	-2.393	0.017	-0.001 -6.08e-05
Unique_Reviewers	-0.0380	0.081	-0.468	0.640	-0.197 0.121