TABLE 3.

Single Simulated Dataset From Scenario 3: Block-Stratified and Pooled Estimation of Vaccine Effectiveness With Logistic Regression and IPTW

Block	Population Size	Sample Size (n. Controls)	Population Vaccination Prevalence, f*	True Values 1 − ψcRR, f*	Logistic Regression, Est (95% CI)	IPTW, Controls, Est (95% CI)
2	250,000	1,832 (31)	0.24	0.76	0.44 (−0.70, 0.77)	0.0 (−2.2, 0.65)
3	250,000	895 (26)	0.32	0.77	0.73 (0.35, 0.88)	0.64 (0.17, 0.84)
1	250,000	523 (48)	0.37	0.77	0.69 (0.38, 0.84)	0.66 (0.34, 0.82)
5	500,000	1,665 (73)	0.58	0.82	0.86 (0.77, 0.92)	0.86 (0.75, 0.92)
4	250,000	346 (38)	0.69	0.84	0.89 (0.77, 0.96)	0.92 (0.81, 0.96)
8	500,000	1,578 (78)	0.75	0.86	0.84 (0.73, 0.91)	0.79 (0.64, 0.88)
10	1,000,000	2,816 (134)	0.77	0.87	0.93 (0.88, 0.96)	0.90 (0.84, 0.94)
9	1,000,000	2,379 (147)	0.78	0.87	0.89 (0.83, 0.93)	0.85 (0.76, 0.90)
6	500,000	1,121 (78)	0.79	0.87	0.88 (0.78, 0.93)	0.84 (0.71, 0.91)
7	500,000	576 (77)	0.83	0.88	0.91 (0.82, 0.96)	0.87 (0.74, 0.94)
Analysis of pooled data, n = 13,731:			Adjusting for X		0.87 (0.84, 0.89)	0.85 (0.81, 0.87)
			Adjusting for block		0.86 (0.84, 0.87)	0.83 (0.80, 0.86)

This analysis was conducted on a single simulated dataset representing a census of hospitalized patients, allowing for a larger sample size in each block. IPTW was implemented with weighted logistic regression where only controls were used to fit the propensity score model. The stratified analyses used 10% weight truncation, but this had negligible impact on the estimates of all blocks except for block 2 where the estimation was unstable due to only having five vaccinated controls.