PROLIFIC: Projection-based Test for Lack of Importance of Smooth Functional Effect in Crossover Design

TL;DR

This paper introduces a projection-based statistical test to evaluate the significance of smooth functional effects in longitudinal functional data, demonstrated through a crossover study on cats' activity levels under medication.

Contribution

It develops a novel pseudo generalized F test for functional treatment effects in crossover designs, accounting for covariates and carryover effects, with proven asymptotic properties.

Findings

Test maintains size in finite samples

Detects significance of medication effect effectively

Outperforms bootstrap-based methods

Abstract

Wearable devices for continuous monitoring of electronic health increased attention due to their richness in information. Often, inference is drawn from features that quantify some summary of the data, leading to a loss of information that could be useful when one utilizes the functional nature of the response. When functional trajectories are observed repeated over time, it is termed longitudinal functional data. This work is motivated by the interest to assess the efficacy of a noninflammatory medication, meloxicam, on the daily activity levels of household cats with a pre-existing condition of osteoarthritis under a crossover design. These activity profiles are recorded at a minute level by accelerometer over the entire study period. To this aspect, we propose an orthogonal projection-based test pseudo generalized F test for significance of the functional treatment effect under a functional additive crossover model after adjusting for the carryover effect and other baseline covariates. Under mild conditions, we derive the asymptotic null distribution of the test statistic when the projection function for the underlying Hilbert space is estimated from the data. In finite sample numerical studies, the proposed test maintains the size, is powerful to detect the significance of the smooth effect of meloxicam, and is very efficient compared to bootstrap-based alternatives.