Adjustment for baseline characteristics in randomized trials using logistic regression: sample-based model versus true model

Table 3 Proportion of treatment effects within ± 0.1 of the true value, for different values of the true treatment effect (β₁) and of sample size, with a strong confounder effect (β₂ = − 1): unadjusted for confounder, adjusted in sample-based model, and adjusted in true model

Sample size	Unadjusted analysis	Adjusted, sample-based model	Adjusted, true model	Unadjusted analysis	Adjusted, sample-based model	Adjusted, true model
	Treatment effect β₁ = 0, continuous confounder			Treatment effect β₁ = 0, binary confounder
2 × 50	0.23	0.19	0.19	0.24	0.19	0.19
2 × 100	0.28	0.27	0.27	0.27	0.26	0.26
2 × 200	0.34	0.37	0.37	0.35	0.37	0.37
2 × 500	0.57	0.56	0.56	0.58	0.56	0.56
2 × 1000	0.73	0.73	0.73	0.73	0.72	0.72
	Treatment effect β₁ = 0.5, continuous confounder			Treatment effect β₁ = 0.5, binary confounder
2 × 50	0.23	0.18	0.19	0.24	0.19	0.19
2 × 100	0.28	0.27	0.27	0.28	0.27	0.27
2 × 200	0.38	0.37	0.37	0.38	0.37	0.37
2 × 500	0.55	0.55	0.55	0.57	0.56	0.56
2 × 1000	0.71	0.72	0.72	0.72	0.72	0.72
	Treatment effect β₁ = 1, continuous confounder			Treatment effect β₁ = 1, binary confounder
2 × 50	0.18	0.17	0.18	0.19	0.18	0.18
2 × 100	0.26	0.25	0.25	0.26	0.26	0.26
2 × 200	0.35	0.35	0.36	0.36	0.36	0.36
2 × 500	0.53	0.53	0.54	0.52	0.54	0.54
2 × 1000	0.66	0.70	0.70	0.66	0.70	0.71

ISSN: 1745-6215