Table 4.

Comparison of proportional odds logistic regression parameter estimates for the post-operative surgical complications data, stratified by gender.

Effect	Approach	Estimate	SE	Z-statistic	P-value
Gender: Male (n = 53)
Intercept (j ≥ 2)	Standard MLa	11.778	208.500	0.06	0.955
	ML:Bias-Corrected	1.920	1.741	1.10	0.272
	Clogg et al.	5.474	8.922	0.61	0.540
Intercept (j = 3)	Standard MLa	13.562	208.500	0.07	0.948
	ML:Bias-Corrected	3.376	1.817	1.86	0.065
	Clogg et al.	7.223	8.946	0.81	0.419
Apgar 3–4	Standard MLa	12.988	208.500	0.06	0.950
	ML:Bias-Corrected	2.858	2.087	1.37	0.173
	Clogg et al.	6.663	8.990	0.74	0.459
Apgar 5–6	Standard MLa	10.170	208.500	0.05	0.961
	ML:Bias-Corrected	0.509	1.890	0.27	0.788
	Clogg et al.	3.889	8.954	0.43	0.664
Apgar 7–8	Standard MLa	9.690	208.500	0.05	0.963
	ML:Bias-Corrected	−0.018	1.852	−0.01	0.992
	Clogg et al.	3.420	8.946	0.38	0.702
Pre-operative	Standard MLa	0.596	0.822	0.72	0.469
Disease	ML:Bias-Corrected	0.545	0.796	0.68	0.495
	Clogg et al.	0.582	0.813	0.72	0.474
Gender: Female (n = 58)
Intercept (j ≥ 2)	Standard MLa	1.938	1.112	1.74	0.081
	ML:Bias-Corrected	1.576	0.972	1.62	0.107
	Clogg et al.	1.905	1.094	1.74	0.082
Intercept (j = 3)	Standard MLa	4.448	1.486	2.99	0.003
	ML:Bias-Corrected	3.584	1.195	3.00	0.003
	Clogg et al.	4.331	1.437	3.01	0.003
Apgar 3–4	Standard MLa	1.833	1.460	1.26	0.209
	ML:Bias-Corrected	1.491	1.330	1.12	0.264
	Clogg et al.	1.797	1.444	1.24	0.213
Apgar 5–6	Standard MLa	1.105	1.234	0.90	0.371
	ML:Bias-Corrected	0.808	1.103	0.73	0.465
	Clogg et al.	1.080	1.217	0.89	0.375
Apgar 7–8	Standard MLa	−0.397	1.298	−0.31	0.760
	ML:Bias-Corrected	−0.514	1.149	−0.45	0.655
	Clogg et al.	−0.379	1.274	−0.30	0.766
Pre-operative	Standard MLa	−0.057	0.788	−0.07	0.943
Disease	ML:Bias-Corrected	−0.023	0.737	−0.03	0.975
	Clogg et al.	−0.054	0.778	−0.07	0.945

^aStandard ML is not bias-corrected, with convergence criterion: relative change in the log-likelihood between successive iterations is less than 0.000001