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We analyse time series from 100 patients with bipolar disorder for correlates of depression symptoms. As the sampling interval is non-uniform, we quantify the extent of missing and irregular data using new measures of compliance and continuity. We find that uniformity of response is negatively correlated with the standard deviation of sleep ratings (ρ = -0.26, p = 0.01). To investigate the correlation structure of the time series themselves, we apply the Edelson-Krolik method for correlation estimation. We examine the correlation between depression symptoms for a subset of patients and find that self-reported measures of sleep and appetite/weight show a lower average correlation than other symptoms. Using surrogate time series as a reference dataset, we find no evidence that depression is correlated between patients, though we note a possible loss of information from sparse sampling.

Original publication

DOI

10.1098/rspb.2013.2320

Type

Journal article

Journal

Proc Biol Sci

Publication Date

07/02/2014

Volume

281

Keywords

bipolar disorder, mood variability, psychiatry, public healthcare, time-series analysis, Affect, Appetite, Bipolar Disorder, Data Interpretation, Statistical, Humans, Models, Biological, Seasons, Sleep, Time Factors