Week Four Flashcards
(15 cards)
Demonstrate that 2 variables are
related or change together.
Association
Determine that the relationship it is
not due to variation in a third
Non-spuriousness
Demonstrate that 1 variable
occurs before another variable.
Temporal Ordering
Correlation describes a statistical association
between two or more variables, meaning they
tend to change together.
Spuriousness
When an apparent relationship between two
variables is the result of third variable
(confounding variable) influencing both or
one of them.
For instance, ice cream sales are
correlated with crime rates.
Best ways to assess spuriousness: use
control variables, direct observation,
longitudinal design.
Non-Spuriousness
A variable that is held constant so that the relationship between
two (or more) other variables can be assessed.
Ways to show that the dependent variable changes due to the
independent variable.
Control Variable
Data collected from at one point in time.
Cross-Sectional
Data collected over multiple points in time
Longitudinal
Longitudinal study in which data are collected from the same
subjects at multiple time points.
Observes same set of individuals changing over time as
opposed to groups.
Panel design (fixed sample)
Type of longitudinal study design in which data are collected
from different members within a particular subpopulation (cohort)
at multiple time points.
Cohort design (AKA event-based)
Relatively inexpensive
No need to recontact subjects
Can be quickly implemented to address current events
and hot-button issues
Cross-Sectional research pros
Cannot assess causal ordering
Cross-Sectional research cons
Can assess causal ordering and change over time
Longitudinal Research Pros
Attrition, or the loss of sample members over time, usually
to death or dropout, in panel studies
Costs are higher.
Longitudinal Research Cons
When a relationship has already been established, but a
third variable explaining the relationship has not been
discovered
For instance,
X—>Y
How does “Z” influence this relationship?
X->Z->Y
Introduce new relationships
What is the order of the relationship?
“Flip relationship on it’s head”
Does the independent variable cause the dependent variable, or
is it the other way around?
Often called “selection effects”
Reverse causation