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. 2020 Oct 19;32(1):101–110. doi: 10.1097/EDE.0000000000001268

TABLE 2.

An Application of At-risk-measure Sampling in an Example Study Estimating the IRR of Bicycle Crashes Comparing Roadway Types in Atlanta, Georgia Between 1 October 2016 and 31 July 2018

Measure Scenario Exposed (95% CI) Unexposed (95% CI) Exposure Ratio (95% CI) IRR (95% CI)
Number of crashes No bias adjustment 104 (73, 140) 25 (15, 38) 4.2 (2.1, 8.2)
Bicycle–distance (person–km) No bias adjustment 1.5 × 106 (1.2 × 106, 1.8 × 106) 1.1 × 106 (0.9 × 106, 1.2 × 106) 1.4 (1.1, 1.9) 3.0 (1.4, 5.9)
Bicycle–distance (person–km) IPSW only 1.3 × 107 (0.5 × 107, 3.0 × 107) 1.0 × 107 (0.3 × 107, 1.9 × 107) 1.3 (1.1, 1.9) 3.1 (1.4, 6.0)
Number of crashes Standardization only 3.4 (1.8, Inf)
Bicycle–distance (person–km) Standardization only 1.4 (1.1, 1.9)
Pseudo-IRa (per sampled person–km) Standardization only 5.6 × 10−5 (3.1 × 10−5, 7.9 × 10−5) 2.3 × 10−5 (0.0, 3.5 × 10−5) 2.4 (1.2, Inf)
Number of crashes IPSW, then standardization 3.5 (1.8, Inf)
Bicycle–distance (person–km) IPSW, then standardization 1.4 (1.1, 2.0)
IR (per estimated person–km) IPSW, then standardization 6.4 × 10−6 (2.2 × 10−6, 19.5 × 10−6) 2.5 × 10−6 (0.0, 8.0 × 10−6) 2.6 (1.2, Inf)

The 95% CI was estimated by the percentile method using nonparametric hierarchical bootstrapping (N, replications = 1,000). For scenarios including IPSW, the 95% CI also considers the uncertainty due to the parametric sampling-fraction model.

Please see text for exposure definition and additional detail.

a

The pseudo-incidence rate is the number of crashes divided by the sampled person–distance, following the terminology on p. 113 of Modern Epidemiology, 3rd Edition.21