Evaluating Causal Claims

These flashcards cover key vocabulary related to evaluating causal claims in research design, focusing on internal validity threats, confounds, and effects that impact the interpretation of data.

Selection Effects

When conditions in between-subjects designs have systematically different participants.

Order Effects

When there’s carryover from one presentation of the independent variable to another.

Design Confounds

When another variable systematically varies with the independent variable.

Internal Validity

The degree to which a study accurately establishes a causal relationship between variables.

Maturation Threat

The changes in the experimental group may occur more or less spontaneously over time.

History Threat

An external event that happens to most everyone in the study between pre-test and post-test.

Regression Threat

A tendency for extreme scores on a variable to move closer to the mean upon retesting.

Attrition Threat

When participants drop out of a study before it ends.

Testing Threats

Changes in a participant's score due to taking the test multiple times.

Instrumentation Threats

Changes in the measurement instrument over time that can affect results.

Demand Characteristics

When participants guess the hypothesis and change their behavior accordingly.

Placebo Effects

Changes in participants' behavior due to their belief they are receiving treatment.

Null Effect

When the independent variable shows no difference in outcome.

Measurement Error

Factors that can inflate or deflate a person’s true score on the dependent variable.

Situation Noise

Irrelevant events or distractions affecting the experiment's outcome.