Internal Validity
 Internal Validity
 Revolves around the question of whether your IV actually caused any change that
you observe in your DV
 Threats to Internal Validity
 Any factor that allows for an alternative explanation
 Extraneous Variables
 Confounding Variables
 The History Threat
 Events that occur between the DV measurements in a repeated measures design
 Distractions in the experimental environment
 Experiences people have between measurements
 Repeated measures designs are most vulnerable to this threat
 The Maturation Threat
 Changes in participants that occur over time during an experiment
 Can refer to long-term changes (aging, cognitive development) during a
longitudinal study
 Can refer to short-term changes (hunger, fatigue, boredom)
 How much time it takes before maturation becomes a threat depends on the
demands placed on participants and other factors (amount of sleep participants
had before beginning, participant motivation, etc)
 The Testing Threat
 Internal validity is threatened when the process of measuring the DV itself causes
a change in the DV
 Practice effect—scores are different when taking a test a second time simply due to have
taken the test before.
 Reactive measures—DV measurements that change the DV being measured
 The Instrumentation Threat
 Occurs when the equipment or human measuring the DV changes the measuring
standard over time
 Measuring equipment malfunction
 Inconsistencies in researcher measurement behavior
 Inter-rater reliability—comparing scores of several raters
 Standardized Scoring practices
 The Threat of Statistical Regression
 Occurs when low scorers improve or high scorers fall on a second administration
of a test due solely to statistical reasons
 Regression to the mean: extreme scorers are likely to move toward the mean
(mean magnetism)
 Example: sample of people who scored very low on the SAT. Statistical
regression says they are likely to score higher next time despite the instructional
intervention given
 Example: sample of basketball players with extremely high free throw accuracy.
Distract them. Lower accuracy. Due to distraction or regression?
 The Threat of Selection
 Choosing participants in such a way that the groups are not equal before the
experiment, thus one cannot be certain that the IV caused any difference we
observe after the experiment.
 Selecting participants because they are already members of a certain group.
 Differences between groups reflect differences that existed between them
BEFORE the presentation of the IV
 Note: A validity threat for true experimental designs, but often done intentionally
in nonexperimental designs.
 The Threat of Mortality
 “Mortality” means death (animals) or dropping out of an experiment (humans)
 Occurs if experimental participants from different groups drop out of the
experiment at different rates (if those from one group drop out at a higher rate
than another group)
 Often happens when the experimental condition is noxious, unpleasant, or
demanding
 Pre-experiment mortality can impact results.
 Example: values-based education, comparing freshmen and seniors. Seniors
report holding stronger values. Due to values-based education or mortality
(people whose values are incongruent with the school’s leave)
 The Threat of Diffusion or
Imitation of Treatments
 Occurs if participants in one treatment group become familiar with the treatment
of another group and copy that treatment
 If participants of one group share information with the other group, the groups
may behave similarly due to having this information
 Example: teaching a study strategy to the 11:00 class and not the 1:00 class, but a
loudmouth in the 11:00 class tells a friend in the 1:00 class about the strategy and
that persons starts using it and telling others. (treatment diffusion—all participants
are using the same treatment)