Analysing covariates with spike at zero: a modified FP procedure and conceptual issues

TY - JOUR

T1 - Analysing covariates with spike at zero: a modified FP procedure and conceptual issues

AU - Becher, Heiko

AU - Lorenz, Eva

AU - Royston, Patrick

AU - Sauerbrei, Willi

N1 - © 2012 WILEY-VCH Verlag GmbH & Co. KGaA, Weinheim.

PY - 2012/9/1

Y1 - 2012/9/1

N2 - 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.

AB - 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.

KW - Alcohol Drinking

KW - Analysis of Variance

KW - Biometry

KW - Breast Neoplasms

KW - Dose-Response Relationship, Drug

KW - Humans

KW - Logistic Models

KW - Models, Statistical

KW - Risk Factors

U2 - 10.1002/bimj.201100263

DO - 10.1002/bimj.201100263

M3 - SCORING: Journal article

C2 - 22778015

VL - 54

SP - 686

EP - 700

JO - BIOMETRICAL J

JF - BIOMETRICAL J

SN - 0323-3847

IS - 5

ER -