Dear all,
on the 14th of December, 16:00 s.t. Regina Siegers from the master of Survey Statistics will speak about her master thesis on the topic given below. You are cordially invited to join via the typical login info of our virtual colloquium given in this vc course.
Best regards
Johannes
VECTOR(S) AND THE SEARCH FOR HAPPINESS:
A COMPARISON OF CONSTRAINT-BASED CAUSAL DISCOVERY METHODS
ON TIME-SERIES DATA FROM MULTIPLE CONTEXTS WITH LATENT VARIABLES
A COMPARISON OF CONSTRAINT-BASED CAUSAL DISCOVERY METHODS
ON TIME-SERIES DATA FROM MULTIPLE CONTEXTS WITH LATENT VARIABLES
This thesis aims to showcase different methods of constraint-based causal discovery using
life-satisfaction data from the World Values Survey. The concepts of graph-based causal
discovery are presented, and three different algorithms are applied to the data. A causal
relationship between financial satisfaction and overall life satisfaction is shown across all
methods. Furthermore, health and the feeling of control over one’s life were identified as
central aspects. However, for a more detailed analysis, the more specific inclusion of the
contexts as well as more precise models for the identification of temporal effects have to be
found.
life-satisfaction data from the World Values Survey. The concepts of graph-based causal
discovery are presented, and three different algorithms are applied to the data. A causal
relationship between financial satisfaction and overall life satisfaction is shown across all
methods. Furthermore, health and the feeling of control over one’s life were identified as
central aspects. However, for a more detailed analysis, the more specific inclusion of the
contexts as well as more precise models for the identification of temporal effects have to be
found.