Chapter 5 - Experimental Research Flashcards
2 fundamentals of experiments
Experiments have two fundamental features. The first is that the researchers manipulate, or systematically vary, the level of the independent variable. The different levels of the independent variable are called conditions.
The second fundamental feature of an experiment is that the researcher exerts control over, or minimizes the variability in, variables other than the independent and dependent variable. These other variables are called extraneous variables.
Manipulate
Changing the level, or condition, of the independent variable systematically so that different groups of participants are exposed to different levels of that variable, or the same group of participants is exposed to different levels at different times.
Single factor two-level design
Independent variables can be manipulated to create two conditions and experiments involving a single independent variable with two conditions are often referred to as a single factor two-level design.
Single factor multi-level design
sometimes greater insights can be gained by adding more conditions to an experiment. When an experiment has one independent variable that is manipulated to produce more than two conditions it is referred to as a single factor multi level design.
Extraneous variables
an extraneous variable is anything that varies in the context of a study other than the independent and dependent variables.
One way to control extraneous variables is to hold them _____.
Constant
Two effects of extraneous variables
Extraneous variables make it difficult to detect the effect of the independent variable in two ways. One is by adding variability or “noise” to the data.
The second way that extraneous variables can make it difficult to detect the effect of the independent variable is by becoming confounding variables. A confounding variable is an extraneous variable that differs on average across levels of the independent variable (i.e., it is an extraneous variable that varies systematically with the independent variable).
To confound means to confuse, and this effect is exactly why confounding variables are undesirable. Because they differ systematically across conditions—just like the independent variable—they provide an alternative explanation for any observed difference in the dependent variable.
2 more ways to control for confounding variables
- Hold them constant
- Randomly assign participants to different conditions.
Randomized clinical trial
An experiment that researches the effectiveness of psychotherapies and medical treatments.
How to control for placebo effects
- Put participants in a placebo control condition.
- Put participants in a waitlist control condition
- Leave out control condition and compare any new treatment with the best available alternative treatment.
4 types of validity
Researchers have focused on four validities to help assess whether an experiment is sound (Judd & Kenny, 1981; Morling, 2014)[1][2]: internal validity, external validity, construct validity, and statistical validity.
Internal validity
An empirical study is said to be high ininternalvalidityif the way it was conducted supports the conclusion that the independent variable caused any observed differences in the dependent variable.
external validity and mundane realism
An empirical study is high inexternalvalidityif the way it was conducted supports generalizing the results to people and situations beyond those actually studied. As a general rule, studies are higher in external validity when the participants and the situation studied are similar to those that the researchers want to generalize to and participants encounter every day, often described asmundane realism.
Psychological realism
Where the same mental process is used in both the laboratory and in the real world.
One of the “big four” validities, whereby the research question is clearly operationalized by the study’s methods.
In addition to the generalizability of the results of an experiment, another element to scrutinize in a study is the quality of the experiment’s manipulations or theconstruct validity.
This conversion from research question to experiment design is calledoperationalization