Background: Nursing research, particularly related to physiological development, often depends on the collection of time series data. The state space approach to time series analysis has great potential to answer exploratory questions relevant to physiological development but has not been used extensively in nursing.
Objectives: The aim of the study was to introduce the state space approach to time series analysis and demonstrate potential applicability to neonatal monitoring and physiology.
Methods: We present a set of univariate state space models; each one describing a process that generates a variable of interest over time. Each model is presented algebraically and a realization of the process is presented graphically from simulated data. This is followed by a discussion of how the model has been or may be used in two nursing projects on neonatal physiological development.
Results: The defining feature of the state space approach is the decomposition of the series into components that are functions of time; specifically, slowly varying level, faster varying periodic, and irregular components. State space models potentially simulate developmental processes where a phenomenon emerges and disappears before stabilizing, where the periodic component may become more regular with time, or where the developmental trajectory of a phenomenon is irregular.
Discussion: The ultimate contribution of this approach to nursing science will require close collaboration and cross-disciplinary education between nurses and statisticians.
Janet A. Levy, PhD, is Assistant Research Professor, School of Nursing, Duke University, Durham, North Carolina.
Heather E. Elser, PhD, RN, NNP-BC, is Assistant Professor, School of Nursing, Duke University, Durham, North Carolina, and Senior Manager of Clinical Operations, QOL Medical, LLC, Raleigh, North Carolina.
Robin B. Knobel, PhD, RN, is Assistant Professor, School of Nursing, Duke University, Durham, North Carolina.
Editor’s note This article is part of the focus on statistics in nursing research.
Accepted for publication September 6, 2012.
The authors have no conflicts of interest to disclose.
Corresponding author: Janet A. Levy, PhD, School of Nursing, Duke University, DUMC 3322, 311 Trent Drive, Durham, NC 27710 (e-mail: email@example.com).