Seasonality, mediation and comparison (SMAC) methods to identify influences on lung function decline

ABSTRACT This study develops a comprehensive method to assess seasonal influences on a longitudinal marker and compare estimates between cohorts. The method extends existing approaches by i) combining a sine-cosine model of seasonality with a specialized covariance function for modeling longitudinal correlation; ii) performing mediation analysis on a seasonality model. An example dataset and R code are provided. The bundle of methods is referred to as seasonality, mediation and comparison (SMAC). The case study described utilizes lung function as the marker observed on a cystic fibrosis cohort but SMAC can be used to evaluate other markers and in other disease contexts. Key aspects of customization are as follows. • This study introduces a novel seasonality model to fit trajectories of lung function decline and demonstrates how to compare this model to a conventional model in this context • Steps required for mediation analyses in the seasonality model are shown • The necessary calculations to compare seasonality models between cohorts, based on estimation coefficients, are derived in the study