Establishing Cause-Effect Relationships
Definition
Cause-Effect Relationships
The relationship between two variables where one variable (the independent variable ) directly influences or causes a change in the other variable (the dependent variable).
The Role of Experiments in Establishing Causality
- Experiments are the gold standard for establishing causality because they allow researchers to manipulate one variable while controlling others.
- This manipulation helps determine if changes in the independent variable lead to changes in the dependent variable.
A classic example is Newcomer et al. (1999), which investigated the effects of cortisol on memory.
This study used a double-blind, placebo-controlled experiment to establish a cause-and-effect relationship between cortisol levels and memory performance.
Key Features of Experiments
Manipulation of Variables
- Independent Variable (IV): The variable that is manipulated by the researcher.
- Dependent Variable (DV): The variable that is measured to see if it is affected by the IV.
In Newcomer et al. (1999), the IV was the level of cortisol administered, and the DV was memory performance.
Randomization
- Random Assignment: Participants are randomly assigned to different conditions to ensure that groups are equivalent at the start of the experiment.
In Newcomer et al. (1999), participants were randomly assigned to one of three conditions:
- High cortisol group: Received 160 mg of cortisol per day.
- Low cortisol group: Received 40 mg of cortisol per day.
- Control group: Received a placebo.
Control Groups
- Control Group: A group that does not receive the experimental treatment, used as a baseline to compare the effects of the IV.
Standardization
- Standardized Procedures: Ensuring that all participants are treated the same way, except for the manipulation of the IV.
In Newcomer et al. (1999), all participants took the same memory test under similar conditions.
How Experiments Establish Causality
- By manipulating the IV and controlling other variables, experiments can demonstrate a direct relationship between the IV and DV.
- This control helps rule out confounding variables that could otherwise explain the results.
