Table 2 |
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|
Data-driven dichotomization1 |
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|
Cutoff |
OR (95% CI) |
|
|
|
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Data-driven dichotomization that is not based on the exposure/outcome association |
||
|
|
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|
Determined by the distribution of exposure variable |
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|
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) |
|
|
||
|
|
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|
Determined by the distribution of outcome variable |
||
|
Equal numbers of exposed and unexposed cases |
27.84 |
1.4 (1.4, 1.5) |
|
|
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|
Effect of a desired precision2 |
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|
Minimizing the standard error |
27.19 |
1.5 (1.4, 1.6) |
|
|
||
|
Maximizing the area under the curve2 |
25.553 |
1.7 (1.6, 1.8) |
|
|
||
|
|
||
|
Association-driven dichotomization |
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|
Effect of a desired size2 |
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|
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) |
|
|
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|
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 Varying the BMI cutoff from the 25th (23.75) and 75th (31.40) percentiles in increments of 0.01. 3 25.55 is also the cutoff with the maximum Youden's J statistic. |
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|
Heavner et al. BMC Medical Research Methodology 2010 10:59 doi:10.1186/1471-2288-10-59 |
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