Methods for significance testing of categorical covariates in logistic regression models after multiple imputation: power and applicability analysis

Table 2 Model estimates of complete data analysis

	Estimate	SE	Z	p-value
Intercept	−8.0215	2.4064	−3.3333	0.0008
Group				0.0516
Group (1)^a	0.7535	0.3287	2.2927	0.0219
Group (2)^a	0.5986	0.3338	1.7936	0.0729
Age	−0.0007	0.0141	−0.0498	0.9602
Gender	0.4247	0.3525	1.2049	0.2282
BMI	0.0619	0.0352	1.7587	0.0786
Education				0.5108
Education (1)^a	−0.1501	0.4058	−0.3699	0.7114
Education (2)^a	−0.3208	0.4397	−0.7297	0.4656
Education (3)^a	−0.5997	0.6829	−0.8782	0.3798
Education (4)^a	−1.2694	0.8117	−1.5639	0.1179
Sitting				0.0195
Sitting (1)^a	0.6305	0.3295	1.9134	0.0557
Sitting (2)^a	−0.3515	0.4795	−0.7329	0.4636
Sitting (3)^a	1.0407	0.5286	1.9690	0.0489
Lifting				0.9830
Lifting (1)^a	0.1441	0.3692	0.3903	0.6963
Lifting (2)^a	0.0574	0.4127	0.1389	0.8894
Lifting (3)^a	0.0990	0.4424	0.2238	0.8229
Vibration tools				0.0090
Vibration tools (1)^a	−0.5406	0.3717	−1.4543	0.1459
Vibration tools (2)^a	0.0554	0.4165	0.1329	0.8942
Vibration tools (3)^a	−1.6335	0.5573	−2.9313	0.0034
Pain at baseline	0.3232	0.0836	3.8656	0.0001
Physical functioning	0.3220	0.1919	1.6778	0.0934
Disability	−0.9110	0.3283	−2.7747	0.0055
Kinesiophobia	0.0299	0.0222	1.3524	0.1762

ISSN: 1471-2288