EMA Flashcards
What is grand mean centering in statistical analysis?
a) A method of centering variables by subtracting the group mean from each observation
b) A method of centering variables by subtracting the grand mean from each observation
c) A method of aggregating data from multiple groups to calculate a single mean value
d) A method of standardizing variables by dividing each observation by the grand mean
B
What is group mean centering in statistical analysis?
a) A method of centering variables by subtracting the group mean from each observation
b) A method of centering variables by subtracting the grand mean from each observation
c) A method of aggregating data from multiple groups to calculate a single mean value
d) A method of standardizing variables by dividing each observation by the group mean
A.
Advantages EMA
Minimizes recall bias
* Maximizes ecological validity
* Efficient and easy way to collect data
* Needs fewer participants than in a traditional survey
* Understands within-person variability
* Understands processes of change including temporal processes (e.g.,
diurnal affective cycles) and carryover effects
* Represents situation-behaviour associations
* Determine the causality between the variable of interest
What is EMA
Repeated sampling of subjects’ current behaviours and
experiences in real time, in subjects’ natural environments
Which centrality measure calculates the average shortest path between a node and all other nodes in the network?
a) Degree centrality
b) Closeness centrality
c) Betweenness centrality
d) Eigenvector centrality
B
Which centrality measure identifies nodes that are most connected to other nodes in the network?
a) Degree centrality
b) Closeness centrality
c) Betweenness centrality
d) Eigenvector centrality
A
Which centrality measure identifies nodes that are most connected to other nodes in the network?
a) Degree centrality
b) Closeness centrality
c) Betweenness centrality
d) Eigenvector centrality
A
What do edges represent in a network analysis?
a) The magnitude of each node in the network
b) The direction of influence between nodes
c) The probability of an edge being present between nodes
d) The clustering coefficient of each node in the network
B
Which centrality measure identifies nodes that act as intermediaries or bridges between other nodes in the network?
a) Degree centrality
b) Closeness centrality
c) Betweenness centrality
d) Eigenvector centrality
C
In network analysis, what do nodes represent?
a) Relationships between variables
b) Strength of connections between variables
c) Observations or variables in the network
d) The average value of variables in the network
C
What do edges represent in a network analysis?
a) The magnitude of each node in the network
b) The direction of influence between nodes
c) The probability of an edge being present between nodes
d) The clustering coefficient of each node in the network
B
