Background: The interpretation of individual laboratory test results requires the availability of population-based reference intervals. In children, reference interval estimation has to consider frequently the strong age-dependency. Generally, for the construction of reference intervals, a sufficiently large number of independent measurement values is required. Data selections from hospitals or cohort studies often comprise dependencies violating the independence assumption.
Methods: In this article, we propose a combination of LMS-like (mean, M; coefficient of variation, S; skewness, λ or L) and resampling methods to overcome this drawback. The former is recommended by the World Health Organization (WHO) for the construction of continuous reference intervals of anthropometric measurements in children. The approach allows the inclusion of dependent measurements, for example, repeated measurements per subject. It also provides pointwise confidence envelopes as a measure of reliability.
Results and conclusions: The combination of LMS-type methods and resampling provides a feasible approach to estimate age-dependent percentiles and reference intervals using unbalanced longitudinal data.
Keywords: LMS method; biological variation; epidemiology; reference intervals, reference limits.