Chapter Ten: Within-Subjects Design Flashcards
Attrition
The differential dropping out of participants from a study; also known as mortality
Baseline Measurement
The initial assessment of a participant at the onset of a study, prior to any intervention or treatment
Behavioural Diary
A self-report data collection strategy where individuals record their behaviours and associated feelings as they occur
Carryover effect
Exposure to earlier experimental conditions influencing responses to subsequent conditions
Counterbalancing
Identifying and using all potential treatment sequences in a within-subjects design
Dependent Means T-Test
A statistic used to determine if there is a statistically significant difference between two related sets of scores; also known as a dependent means t-test or a paired-samples t-test
Fatigue Effect
Deterioration in quality of measurements due to participants becoming tired, less attentive, or careless during the course of the study
History
A threat to the internal validity of a study due to an external event potentially influencing participants’ behaviour during the study
Instrumentation Problem
In terms of threats to internal validity, a change in how a variable is measured or administered during the course of a study
Latin Square Design
A counterbalancing strategy where each experimental condition appears at every position in the sequence order equally often
Maturation
A threat to the internal validity of a study stemming from either long-term or short-term physiological changes occurring naturally within the participants that may influence the dependent variable
Order Effect
A threat to the internal validity in a within-subjects design resulting from influence that the sequence of experimental conditions can have on the dependent variable
Practice Effect
Changes in a participant’s responses or behaviour due to increased experience with the measurement instrument, not the variable under investigation
Pretest-Posttest Design
A within-subjects design where participants are measured before and after exposure to a treatment or intervention
Repeated-Measures Analysis of Variance (Repeated-Measures ANOVA)
A statistic used to test a hypothesis from a within-subjects design with three or more conditions