SymptomData

In this depression symptoms data, a patient reported for each week on the presence
and absence of eight depression symptoms. The dataset contains the reports of the
eight variables for 145 subsequent weeks.

datasets

The ConNEcT approach investigates the pairwise association strength of binary time series by calculating contingency measures and depicts the results in a network. The package includes features to explore and visualize the data. To calculate the pairwise concurrent or temporal sequenced relationship between the variables, the package provides seven contingency measures (proportion of agreement, classical & corrected Jaccard, Cohen's kappa, phi correlation coefficient, odds ratio, and log odds ratio), however, others can easily be implemented. The package also includes non-parametric significance tests, that can be applied to test whether the contingency value quantifying the relationship between the variables is significantly higher than chance level. Most importantly this test accounts for auto-dependence and relative frequency.See Bodner et al.(2021) <doi: 10.1111/bmsp.12222>.Finally, a network can be drawn. Variables depicted the nodes of the network, with the node size adapted to the prevalence. The association strength between the variables defines the undirected (concurrent) or directed (temporal sequenced) links between the nodes. The results of the non-parametric significance test can be included by depicting either all links or only the significant ones. Tutorial see Bodner et al.(2021) <doi:10.3758/s13428-021-01760-w>.

Nadja Bodner

ConNEcT

Contingency Measure-Based Networks for Binary Time Series

Eva Ceulemans

SymptomData function

A data frame with 145 rows and 8 variables:<dl class="dl-horizontal">
<dt>Core</dt><dd>core depression symptoms including depressed mood and/or diminished interest</dd>
<dt>Energy</dt><dd>lack of energy</dd>
<dt>Eat</dt><dd>eating problems and weight loss or gain</dd>
<dt>Sleep</dt><dd>sleeping problems including hyposomnia or hypersomnia</dd>
<dt>Motor</dt><dd>psychomotor problems</dd>
<dt>Guilt</dt><dd>feelings of guilt</dd>
<dt>Cogn</dt><dd>cognitive problems</dd>
<dt>Death</dt><dd>preoccupation with death</dd></dl>

SymptomData: Depression symptom dataset

Description

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