No rationale for 1 variable per 10 events criterion for binary logistic regression analysis

Table 4 Results simulation study IIb

Estimator	\({\beta _{1}^{F}}\)	\(\beta _{1}^{ML} \)	\(\beta _{1}^{ML} \)	\(\beta _{1}^{ML} \)	\(\beta _{1}^{ML} \)	\(\beta _{1}^{ML} \)	\(\beta _{1}^{ML} \)
Separation detection	NA	Tracing^b	Estimate^c	None	None	None	None
Convergence criterion^a	Default	Default	Default	Default	Type I	Type II	Type III
Data sets removed (%)	0	8.06	16.64	5.12	0.34	6.29	0.09
Bias	0.012	0.569	0.186	1.672	17.5	0.856	41.3
Coverage 90% CI	0.919	0.949	0.937	0.944	0.947	0.944	0.947
Mean width 90% CI	4.32	4.50	3.64	5018	13620	6.03	1135784
MSE	1.080	2.681	0.904	71.563	11532	319	173726

^adefault: tol: 1e-8, max-iter: 25, Type I: tol: 1e-6, max-iter: 25, Type II: tol: 1e-10, max-iter:25, Type III: tol: 1e-10, max-iter:50
^bcriterion: re-estimation process, variance of scaled standard errors >20 (see Appendix)
^acriterion: if for any parameter \(j \neq 0, |\hat {\beta }_{j}|\) >log(50)

ISSN: 1471-2288