Analysing covariates with spike at zero: a modified FP procedure and conceptual issues.
In epidemiology and in clinical research, risk factors often have special distributions. A common situation is that a proportion of individuals have exposure zero, and among those exposed, we have some continuous distribution. We call this a 'spike at zero'. Examples for this are smoking, duration of breastfeeding, or alcohol consumption. Furthermore, the empirical distribution of laboratory values and other measurements may have a semi-continuous distribution as a result of the lower detection limit of the measurement. To model the dose-response function, an extension of the fractional polynomial approach was recently proposed. In this paper, we suggest a modification of the previously suggested FP procedure. We first give the theoretical justification of this modified procedure by investigating relevant distribution classes. Here, we systematically derive the theoretical shapes of dose-response curves under given distributional assumptions (normal, log normal, gamma) in the framework of a logistic regression model. Further, we check the performance of the procedure in a simulation study and compare it to the previously suggested method, and finally we illustrate the procedures with data from a case-control study on breast cancer.
Institute of Public Health, Medical Faculty, University of Heidelberg, Im Neuenheimer Feld 324, 69120 Heidelberg, Germany. heiko.becher@urz.uni-heidelberg.de
Heiko
H
Becher
Eva
E
Lorenz
Patrick
P
Royston
Willi
W
Sauerbrei
D000428:Alcohol Drinking / Q000009:adverse effects; D000704:Analysis of Variance; D001699:Biometry; D001943:Breast Neoplasms / Q000453:epidemiology / Q000209:etiology; D004305:Dose-Response Relationship, Drug; D006801:Humans; D016015:Logistic Models; D015233:Models, Statistical; D012307:Risk Factors