Complexity / 2018 / Article / Tab 1

Research Article

Spread the Joy: How High and Low Bias for Happy Facial Emotions Translate into Different Daily Life Affect Dynamics

Table 1

Description and operationalization of the seven hypotheses tested with the permutation tests.

DescriptionPermutation test

Hypothesis 1JOY and POS are stronger predictors in the network of the high happy bias group than in the network of the low happy bias group(1) The total summed absolute edge weight of all outgoing edges from JOY and POS at time to all nodes in the network at time (including autoregressive edges) is larger for the high happy bias group than for the low happy bias group

Hypothesis 2JOY and POS more strongly predict themselves (i.e., are more easily sustained over time) and each other (i.e., more carry-over between JOY and POS) over time in the high happy bias group than in the low happy bias group(2) The total summed edge weight of all outgoing edges from JOY and POS at time to JOY and POS at time (including autoregressive edges) is larger for the high happy bias group than for the low happy bias group

Hypothesis 3JOY and POS more strongly predict the negative nodes (i.e., larger dampening effect on negative nodes) over time in the high happy bias group than in the low happy bias group(3) The total summed edge weight of all outgoing edges from JOY and POS at time to SAD, IRR, WOR, and NEG at time is larger for the high happy bias group than for the low happy bias group

Hypothesis 4The negative nodes are stronger predictors in the network of the low happy bias group than in the network of the high happy bias group(4) The total summed absolute edge weight of all outgoing edges from SAD, IRR, WOR, and NEG at time to all nodes in the network at time (including autoregressive edges) is larger for the low happy bias group than for the high happy bias group

Hypothesis 5The negative nodes more strongly predict themselves (i.e., are more easily sustained over time) and each other (i.e., more carry-over between the negative nodes) over time in the low happy bias group than in the high happy bias group(5) The total summed edge weight of all outgoing edges from SAD, IRR, WOR, and NEG at time to SAD, IRR, WOR, and NEG at time (including autoregressive edges) is larger for the low happy bias group than for the high happy bias group

Hypothesis 6More pronounced negative associations between negative nodes and JOY and POS (i.e., larger dampening effect on JOY and POS) over time in the low happy bias group than in the high happy bias group(6) The total summed edge weight of all outgoing edges from SAD, IRR, WOR, and NEG at time to JOY and POS at time is larger for the low happy bias group than for the high happy bias group

Hypothesis 7JOY and POS more strongly predict INT in the high than in the low happy bias group(7) The total summed edge weight of all outgoing edges from JOY and POS at time to INT at time is larger for the high happy bias group than for the low happy bias group

JOY = feeling joyful; POS = pleasant experiences; INT = feeling interested in the things around me; SAD = feeling sad; IRR = feeling irritated; WOR = worrying; NEG = unpleasant experiences.