A three-step estimation procedure using local polynomial smoothing for inconsistently sampled longitudinal data.

ABSTRACT: Parametric mixed-effects models are useful in longitudinal data analysis when the sampling frequencies of a response variable and the associated covariates are the same. We propose a three-step estimation procedure using local polynomial smoothing and demonstrate with data where the variables to be assessed are repeatedly sampled with different frequencies within the same time frame. We first insert pseudo data for the less frequently sampled variable based on the observed measurements to create a new dataset. Then standard simple linear regressions are fitted at each time point to obtain raw estimates of the association between dependent and independent variables. Last, local polynomial smoothing is applied to smooth the raw estimates. Rather than use a kernel function to assign weights,

SUBMITTER: Ye L 

PROVIDER: S-EPMC4961582 | biostudies-literature | 2016 Sep

REPOSITORIES: biostudies-literature