This is the code and data to reproduce the main analyses of the first dataset reported in Bringmann, L. F., Pe, M. L., Vissers, N., Ceulemans, E., Borsboom, D., Vanpaemel, W., Tuerlinckx, F., & Kuppens, P. (2016). Assessing temporal emotion dynamics using networks. Assessment, 23, 425-435. doi:10.1177/1073191116645909.
The dataset can be found in the file Data95.csv. To use this data set in Matlab, open the Data95.csv file in Matlab, click on "import numeric matrix" and then on "import selection", which will create Data95 in the workspace. Alternatively, you could load Data95.mat directly in Matlab, which is included for convenience.
To reproduce the main analyses, you should both run replication_code_data95.m (in Matlab) and replication_code_data95.R (in R). The multilevel-VAR analyses were done in Matlab (see replication_code_data95.m.) This script calls data_to_text.m (which should be saved in the same directory) to save the fixed and random effects as text files (e.g., modelfixed1.txt and modelrandom1.txt). For convenience, the necessary output from replication_code_data95.m is included. This output is then further processed in R (see replication_code_data95.R) to create 1) the fixed effects network (i.e., Figure 2), 2) the density table (i.e., Table 1), 3) the centrality tables (i.e., Tables 2 and 3), and the self loops table (i.e., Table 4).
