A distributional approach to obtain adjusted comparisons of proportions of a population at risk

Sauzet O, Breckenkamp J, Borde T, Brenne S, David M, Razum O, Peacock JL (2016)
Emerg Themes Epidemiol 13: 8.

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Journal Article | Original Article | Published | English
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Abstract
Background Dichotomisation of continuous data has statistical drawbacks such as loss of power but may be useful in epidemiological research to define high risk individuals. Methods We extend a methodology for the presentation of comparison of proportions derived from a comparison of means for a continuous outcome to reflect the relationship between a continuous outcome and covariates in a linear (mixed) model without losing statistical power. The so called “distributional method” is described and using perinatal data for illustration, results from the distributional method are compared to those of logistic regression and to quantile regression for three different outcomes. Results Estimates obtained using the distributional method for the comparison of proportions are consistently more precise than those obtained using logistic regression. For one of the three outcomes the estimates obtained from the distributional method and from logistic regression disagreed highlighting that the relationships between outcome and covariate differ conceptually between the two models. Conclusion When an outcome follows the required condition of distribution shift between exposure groups, the results of a linear regression model can be followed by the corresponding comparison of proportions at risk. This dual approach provides more precise estimates than logistic regression thus avoiding the drawback of the usual dichotomisation of continuous outcomes.
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Article Processing Charge funded by the Deutsche Forschungsgemeinschaft and the Open Access Publication Fund of Bielefeld University.
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Sauzet O, Breckenkamp J, Borde T, et al. A distributional approach to obtain adjusted comparisons of proportions of a population at risk. Emerg Themes Epidemiol. 2016;13:8.
Sauzet, O., Breckenkamp, J., Borde, T., Brenne, S., David, M., Razum, O., & Peacock, J. L. (2016). A distributional approach to obtain adjusted comparisons of proportions of a population at risk. Emerg Themes Epidemiol, 13, 8. doi:10.1186/s12982-016-0050-2
Sauzet, O., Breckenkamp, J., Borde, T., Brenne, S., David, M., Razum, O., and Peacock, J. L. (2016). A distributional approach to obtain adjusted comparisons of proportions of a population at risk. Emerg Themes Epidemiol 13, 8.
Sauzet, O., et al., 2016. A distributional approach to obtain adjusted comparisons of proportions of a population at risk. Emerg Themes Epidemiol, 13, p 8.
O. Sauzet, et al., “A distributional approach to obtain adjusted comparisons of proportions of a population at risk”, Emerg Themes Epidemiol, vol. 13, 2016, pp. 8.
Sauzet, O., Breckenkamp, J., Borde, T., Brenne, S., David, M., Razum, O., Peacock, J.L.: A distributional approach to obtain adjusted comparisons of proportions of a population at risk. Emerg Themes Epidemiol. 13, 8 (2016).
Sauzet, Odile, Breckenkamp, Jürgen, Borde, Theda, Brenne, Silke, David, Matthias, Razum, Oliver, and Peacock, Janet L. “A distributional approach to obtain adjusted comparisons of proportions of a population at risk”. Emerg Themes Epidemiol 13 (2016): 8.
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24 References

Data provided by Europe PubMed Central.

Dichotomizing continuous outcome variables: dependence of the magnitude of association and statistical power on the cutpoint
Ragland DR., 1992
The cost of dichotomising continuous variables.
Altman DG, Royston P., BMJ 332(7549), 2006
PMID: 16675816
Odd odds interactions introduced through dichotomisation of continuous outcomes.
Breitling LP, Brenner H., J Epidemiol Community Health 64(4), 2010
PMID: 19692723
Dichotomising continuous data while retaining statistical power using a distributional approach.
Peacock JL, Sauzet O, Ewings SM, Kerry SM., Stat Med 31(26), 2012
PMID: 22865598

Casella G, Berger RL., 1990
Comparison of Perinatal Data of Immigrant Women of Turkish Origin and German Women - Results of a Prospective Study in Berlin.
David M, Borde T, Brenne S, Ramsauer B, Henrich W, Breckenkamp J, Razum O., Geburtshilfe Frauenheilkd 74(5), 2014
PMID: 25089056
Smoking during pregnancy among Turkish immigrants in Germany-are there associations with acculturation?
Reiss K, Breckenkamp J, Borde T, Brenne S, David M, Razum O., Nicotine Tob. Res. 17(6), 2015
PMID: 25468901

AUTHOR UNKNOWN, 0
Dichotomisation using a distributional approach when the outcome is skewed.
Sauzet O, Ofuya M, Peacock JL., BMC Med Res Methodol 15(), 2015
PMID: 25902850
A global reference for fetal-weight and birthweight percentiles.
Mikolajczyk RT, Zhang J, Betran AP, Souza JP, Mori R, Gulmezoglu AM, Merialdi M., Lancet 377(9780), 2011
PMID: 21621717

AUTHOR UNKNOWN, 0

Koenker R., 2005

AUTHOR UNKNOWN, 0

AUTHOR UNKNOWN, 0
On the importance--and the unimportance--of birthweight.
Wilcox AJ., Int J Epidemiol 30(6), 2001
PMID: 11821313

AUTHOR UNKNOWN, 0
Logistic regression: why we cannot do what we think we can do, and what we can do about it
Mood C., 2010
Misclassification
Gustafson P, Greenland S., 2014

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