Case Studies, Small N Designs, and developmental designs Flashcards
Case Study
-Provides a detailed description of an individual
-Observational
-Includes:
-Interview
-Physiological Recording
-Behavioral Tasks
-Psychological Tests
Advantages:
-Detailed Info
-Permits investigation of otherwise impractical or unethical situations
Disadvantages:
-Internal and external validity
Small N Designs
Advantages:
-Able to study rare issues
-Higher internal validity than some (e.g, case study)
-Practical
-Led to cool discoveries
Disadvantages:
-Not as high internal validity as a randomized experimental design
-Can lack external validity for generalizing to population
Small N Design: Single case baseline
-Outcome (usually a behavior) is assessed during a baseline period, then manipulation is added, and outcome is assessed
-Higher Validity than case study but still many confounds
-History and maturation
Small N Design: Multiple Baseline
-Across subjects:
-Observe change with multiple people where the treatment has been given at different times
-Across Behaviors
-Across situations
-Home v. Work
Small N Design: Reversal
-Giving and then removing the treatment
-ABA
-ABAB
-Higher internal validity
Small N Design: Multiple-Component Designs
-ABC, ABCD
-Add more treatment types/comparison conditions
(Placebo)
-Issues
-Order effects but can be addressed with reversal
Developmental Research Design: Cross-Sectional
-Separate groups into cohorts and test something at one point in time
Developmental Research Design: Longitudinal
-A sample is observed at different times as they age
Sequential/Cohort-Sequential
-Part longitudinal and part cross-sectional
-Cohorts but over time
Attrition
-People leaving the study
Random v. Non-Random
-If attrition is random, you only have to worry about reducing sample size
-If attrition is not random it might affect results and conclusions might not be valid
Developmental Research Design: Trend Design
-Data are collected at two or more points in time from different samples of same population
Steps:
1. Collect data from a sample from population at T1
2. Time passes, some people leave population and others enter it (e.g, college students graduating and new students starting)
3. At T2, a different sample is drawn from population