Applications of temporal kernel canonical correlation analysis in adherence studies

Publication Date

2015

Journal Title

Stat Methods Med Res

Abstract

Adherence to medication is often measured as a continuous outcome but analyzed as a dichotomous outcome due to lack of appropriate tools. In this paper, we illustrate the use of the temporal kernel canonical correlation analysis (tkCCA) as a method to analyze adherence measurements and symptom levels on a continuous scale. The tkCCA is a novel method developed for studying the relationship between neural signals and hemodynamic response detected by functional MRI during spontaneous activity. Although the tkCCA is a powerful tool, it has not been utilized outside the application that it was originally developed for. In this paper, we simulate time series of symptoms and adherence levels for patients with a hypothetical brain disorder and show how the tkCCA can be used to understand the relationship between them. We also examine, via simulations, the behavior of the tkCCA under various missing value mechanisms and imputation methods. Finally, we apply the tkCCA to a real data example of psychotic symptoms and adherence levels obtained from a study based on subjects with a first episode of schizophrenia, schizophreniform or schizoaffective disorder.

Document Type

Article

EPub Date

2015/08/22

Status

Faculty, Northwell Researcher

Facility

School of Medicine; Northwell Health

Primary Department

Psychiatry

Additional Departments

Molecular Medicine

PMID

26294330

DOI

10.1177/0962280215598805

For the public and Northwell Health campuses

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