Nonlinear Fractional Polynomials for Estimating Long-Term Persistence of Induced Anti-HPV Antibodies: A Hierarchical Bayesian Approach
Mehreteab Aregay
Ziv Shkedy
Geert Molenberghs
Marie-Pierre David
Fabian Tibaldi
10.6084/m9.figshare.1004797.v2
https://tandf.figshare.com/articles/dataset/Nonlinear_Fractional_Polynomials_for_Estimating_Long_Term_Persistence_of_Induced_Anti_HPV_Antibodies_A_Hierarchical_Bayesian_Approach/1004797
<div><p>When the true relationship between a covariate and an outcome is nonlinear, one should use a nonlinear mean structure that can take this pattern into account. In this article, the fractional polynomial modeling framework, which assumes a prespecified set of powers, is extended to a nonlinear fractional polynomial framework (NLFP). Inferences are drawn in a Bayesian fashion. The proposed modeling paradigm is applied to predict the long-term persistence of vaccine-induced anti-HPV antibodies. In addition, the subject-specific posterior probability to be above a threshold value at a given time is calculated. The model is compared with a power-law model using the deviance information criterion (DIC). The newly proposed model is found to fit better than the power-law model. A sensitivity analysis was conducted, from which a relative independence of the results from the prior distribution of the power was observed. Supplementary materials for this article are available online.</p></div>
2014-08-27 21:13:13
nonlinear
fractional
polynomials
estimating
persistence
induced
anti-hpv
hierarchical
Bayesian