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Table 2 Data-driven dichotomization1

From: Dichotomization: 2 × 2 (×2 × 2 × 2...) categories: infinite possibilities

  Cutoff OR (95% CI)
Data-driven dichotomization that is not based on the exposure/outcome association   
   Determined by the distribution of exposure variable   
Mean BMI 28.16 1.4 (1.3, 1.5)
Median BMI 27.13 1.5 (1.4, 1.6)
75th percentile for BMI 31.40 1.1 (1.1, 1.2)
   Determined by the distribution of outcome variable   
Equal numbers of exposed and unexposed cases 27.84 1.4 (1.4, 1.5)
   Effect of a desired precision 2   
Minimizing the standard error 27.19 1.5 (1.4, 1.6)
   Maximizing the area under the curve 2 25.55 3 1.7 (1.6, 1.8)
Association-driven dichotomization   
   Effect of a desired size 2   
Maximizing the OR 23.79 1.9 (1.8, 2.0)
Minimizing the OR 31.38 1.1 (1.1, 1.2)
OR closest to 1.0 31.38 1.1 (1.1, 1.2)
  1. 1 Comparing those with a value ≥ the cutoff to those with a value < the cutoff. ORs measuring the association between BMI and high cholesterol (≥200 mg/dl) were obtained from logistic regression.
  2. 2 Varying the BMI cutoff from the 25th (23.75) and 75th (31.40) percentiles in increments of 0.01.
  3. 3 25.55 is also the cutoff with the maximum Youden's J statistic.