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Non-experimental Designs

Non-experimental Designs. Psyc 231: Research Methods. Non-experimental Designs. Surveys Developmental Designs Small N Designs Quasi-experiments. Developmental Designs. Used to study development or changes in behavior Describe relationship between age and other variables Three main types

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Non-experimental Designs

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  1. Non-experimental Designs Psyc 231: Research Methods

  2. Non-experimental Designs • Surveys • Developmental Designs • Small N Designs • Quasi-experiments

  3. Developmental Designs • Used to study development or changes in behavior • Describe relationship between age and other variables • Three main types • Cross-sectional • Longitudinal • Cohort-sequential

  4. Cross-sectional Designs • Uses a separate group of participants for each age group being compared • Different groups measured once and compared to each other • Between subjects design • Most commonly used

  5. Cross-sectional Designs • Study the development of memory over time • All three age groups tested at one point in time Age 4 Age 7 Age 11

  6. Cross-sectional Designs • Advantages • Short period of time • No real commitment • Gather all data at one time

  7. Cross-sectional Designs • Disadvantages • Cohort/Generation effects • Does not tell real development of individual • Cannot infer causality

  8. Longitudinal Designs • Same participants are observed over time • Assesses stability of traits • Individuals are compared to self throughout repeated measures over time • Within subjects design

  9. Longitudinal Designs • Study of the development of memory over time • Same participants tested over time Age 4 Age 7 Age 11

  10. Longitudinal Designs • Advantages • No generation effects • Examine individual differences • Can see developmental changes

  11. Longitudinal Designs • Disadvantages • Very time consuming and costly • Hard to find patient participants – Subject Attrition/Mortality • Researchers lose interest • Practice effects • Cross-generational effects • Conclusions based on members of one generation may not apply to other generations • Cannot determine causality

  12. Longitudinal Designs • Wisconsin Longitudinal Study (WLS) • Began in 1957 and is still on-going (50 years) • Originally studied plans for college after graduation • Now it can be used as a test of aging and maturation

  13. Cohort-sequential Designs • Measure groups of participants as they age • Combines the best features of both longitudinal and cross-sectional designs • Studies specific age groups over time • Both between and within subjects design

  14. Cohort-sequential Designs • Study of the development of memory over time • Test multiple age groups over time Age 4 Age 8 Age 8 Age 12 Age 12 Age 16

  15. Cohort-sequential Designs • Advantages • Saves time • Get more information • Long-term effects and developmental changes • Compare to different ages • No generation effects

  16. Cohort-sequential Designs • Disadvantages • More time consuming than cross-sectional • Does not mean causation

  17. Small N Designs • Study one or few participants (typically 3-8 participants) • Each individual is analyzed separately • Common type of design until 1920’s • Still used in some areas of research: clinical settings, phenomenon • Different from case studies

  18. Small N Designs • Typically observe participants • Baseline studies • Effect doesn’t occur before IV (baseline) • Show that effect occurs with IV (treatment) • Doesn’t occur without IV (reversibility) • Observation/testing generally occurs at 3 points • Before treatment, after treatment, after reverse treatment • Examine level and trend to determine effect

  19. Small N Designs • Level • How frequent or intense is the behavior? • Are the data points high or low? • Trend • Does the behavior increase or decrease? • Are the data points flat or on a slope?

  20. Small N Designs • ABA design (baseline, treatment, baseline) • Must be able to reverse effect • Could not have been due to maturation, history, etc. • Effectiveness of a drug

  21. Small N Designs • Advantages • Focus on individual performance • Can see big effects • Avoid some ethical problems (non-treatments/controls) • Allows to look at unusual (and rare) types of subjects • Often used to supplement large N studies, with more observations on fewer subjects

  22. Small N Designs • Disadvantages • Generalizability • Effects may be small relative to variability of situation • Some effects are by definition between subjects • Treatment can lead to a lasting change, so you don’t get reversals • Ethical issues with reversing treatment

  23. Small N Designs • Hermann Ebbinghaus (1885) studied memory of nonsense syllables on himself • Discovered the forgetting curve and learning curve • Know a lot about memory today because of him

  24. Quasi-experimental Designs • Almost “true” experiments but lack of control over assignment of participants • Independent variable cannot be manipulated (inherent confound) • Subject variable • Time could be variable (Developmental) • Random variable already present

  25. Quasi-experimental Design s • Advantages • Allows applied research when experiments not possible • Threats to internal validity can (sometimes) be assessed • Practical and more feasible than true experiments, especially in clinical settings • Some generalizability

  26. Quasi-experimental Designs • Disadvantages • Difficult to make clear cause-and-effect statements • Statistical analysis can be difficult • Most statistical analyses assume randomness • Can not randomize assignment to groups

  27. Quasi-experimental Designs • Common types • Non-equivalent control groups design • Time series designs • Interrupted time series design • Control group interrupted time series design

  28. Independent Variable Dependent Variable Dependent Variable Non-Random Assignment Experimental group Measure Measure participants Control group Measure Measure Quasi-experimental Designs • Non-equivalent control groups design • Typically used as a pretest-posttest • Assignment based on already established variable • Between subjects design

  29. Quasi-experimental Designs • Non-equivalent control groups design: Pretest-posttest • Example • Individuals high on self-esteem and low on self-esteem • Pretested on depression levels • Intervention given to low self-esteem group • Posttested on depression levels

  30. Quasi-experimental Designs • Time series designs • Interrupted times series design • Observe on several occasions before and after the independent variable occurs • Within subjects design obs obs obs Treatment obs obs obs • The pretest observations allow the researcher to look for pre-existing trends • The posttest observations allow the researcher to look for changes in the trends

  31. Quasi-experimental Designs • Time series designs • Control group interrupted time series design • A variation of the interrupted time series designs • Series of observations followed by treatment for experimental condition • Compared to a control group obs obs obs Treatment obs obs obs obs obs obs obs obs obs

  32. Questions?

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