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Research Psych
Final Exam Study - Specialized Designs
| Question | Answer |
|---|---|
| What are the two most common types of additional specialized research designs? | Developmental Designs and Small-N Designs |
| What are the three main developmental designs? | Longitudinal designs, cross-sectional designs, and cohort-sequential designs. |
| What is a longitudinal research design? | A developmental design where one sample of participants is followed over time and tested at different ages. Longitudinal designs treat age as a within-subjects variable b/c each participant provides observations at each of the ages tested in the study |
| Cons of using a longitudinal research design | It takes time to wait for the participants to age, attrition/mortality, testing effects may occur with multiple testings of the same participants. |
| What is a cross-sectional design? | A developmental design where age is treated as a between-subjects variable and different groups of participants at different ages are tested only once for their age at the time of the study. |
| Pros of using a cross-sectional design | Each participant is tested only once, which reduced the chance of attrition. Also, the study can be completed more quickly with a cross-sectional than with a longitudinal design. |
| Cons of using a cross-sectional design | Generation effects/cohort effects can affect the results due to different experiences that different generations have |
| What is a cohort-sequential design? | A developmental design where multiple samples of participants of different ages are followed over time and tested at different ages. |
| Pros of using a cohort-sequential design | It will allow researchers to compare ages quickly with the first testing of the different aged samples. Additionally, generation effects may be less problematic. Thus, in most cases this design is preferable to a longitudinal and cross-sequential design. |
| What is a small-n design? | An experiment conducted with one or a few participants to better understand the behavior of those individuals |
| Pros to using a small-n design | Using a large number of observations reduces the error in the data and makes it easier for a researcher to detect an effect of an independent variable. Also makes it easier for a researcher to control for extraneous factors. Increase internal validity |
| Cons to using a small-n design | Results cannot always be generalized to people outside the study. Cannot be used to measure many types of behavior. Carryover effects may occur |
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cassidylm34
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