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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.
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BMC Medical Research Methodology

ISSN: 1471-2288

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