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41 Cards in this Set
- Front
- Back
Quasi-experiments |
Experimenter doesn't directly manipulate variables Variable are selected |
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Natural Treatment Design |
Design: observation to treatment to observation E.G. effect of new curriculum on 3rd grade achievement Note: this is not a true reversal (ABA) design |
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Natural Treatment Problems (potential confounds) |
Maturation-changes in the participants themselves (e.g., experience with tests, better social adjustment, biological maturation) History-influences outside the classroom that could affect results |
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Natural Treatment Solutions |
Use nonequivalent control group But No random assignment Matching after the fact; therefore, selection bias |
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One-shot case studies Design and Problems |
Design: History to current behavior E.G. Clinical Case Problem: No baseline observations Thus, no control condition |
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One-shot case studies Solutions |
Use Deviant Case Analysis Similar individual without treatment, as control Need many observations and good detective work e.g., suppose patient is depressed; history shows
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Interrupted-Time Series Design |
Does Flouride cause increased achievement? Third variable problem (e.g., absenteeism) Use nonequivalent control group Examine several dependent variables Other sources of confounding: Other changes that occurred Mortality (not same subjects before and after the tests) |
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Designs Employing Subject Variables |
Subject Variable Some measurable characteristic of people (I.Q., sex, age, race, addiction, mental illness) Always confounded with other variables i.e., can't manipulate subject variable while holding other factors constant Use matching to control for confounded variables e.g., compare schizophrenics to neurotics of similar age, I.Q., length of hospitalization etc. |
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Designs Employing Subject Variables Problems with matching |
Relevant variables may be unknown May result in small n's Subtle interactions among matching variables may confound results Regression artifacts |
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Designs Employing Subject Variables Age as a variable |
Cross sectional Design e.g., compare 5,8, and 12 year olds Problem: age confounded with generation of birth (different attitudes, education, etc.) |
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Designs Employing Subject Variables Longitudinal Design |
Same subjects studied over time Problem: age confounded with time of testing |
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Designs Employing Subject Variables Time lag Design |
Examines time of testing while holding age constant Problem: confounding time of testing with generation gap |
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Designs Employing Subject Variables Cross-sequential Design |
Test 2 or more age groups at 2 or more times Includes features of other three designs Different ages tested at the same time (cf X- sect.) Same subjects tested successively (cf longitudinal) Different subjects of same age tested at different times (cf time lag) Therefore, can determine effects of major confoundings |
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Designs Employing Subject Variables Alternative |
Cross Sectional design with age as quasi-independent variable plus another true independent variable Look for interaction: e.g., effect of two learning strategies and age on memory If interaction between strategy and age, try to determine what variable confounded with age is responsible |
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Designs Employing Subject Variables Protocol 1 |
Age 5 yr Memory Test 12 yr Memory Test Results: 12 year old > 5 year old Interpretation: Brain Maturation? Education? Reading Level? Motivation? Experience? etc. |
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Designs Employing Subject Variables Protocol 2 |
Age: Training: 5 yr. Rote vs. Categorization vs None 12 yr. Rote vs. Categorization vs None Memory Test Results: Rote: 5 year old > 12 year old Categ.: 12 year old > 5 year old None: 12 year old > 5 year old What variable associated with age accounts for interaction? |
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Operant Conditioning Basic Paradigm |
Basic Paradigm: R to SR+ to increasing probability of R Importance of controlled environment (skinner box) Focus on rate of response |
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Operant Conditioning Importance of schedule of reinforcement |
Strongly influences temporal pattern of response Generality established Across different species Across different responses Across different reinforcers |
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Operant Conditioning Focus on behavior of individual subjects |
Reliability demonstrated by stabililty of baseline Across sessions Across individuals Group comparisons not used No group means No tests of statistical significance |
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Operant Conditioning Applications |
Behavior modification Programmed learning Behavioral pharmacology |
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Operant Conditioning The Reversal Design (ABA) |
(A) Baseline (B) Independent Variable (A) Baseline |
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Operant Conditioning Multiple-Baseline Design |
If permanent carry over effects |
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Interpreting Results |
Interpreting specific results Scale attenuation effects Types A) Ceiling effects B) Floor effects Causes a) scale of measurement not broad enough b) task difficulty (too easy or too hard) Take home message- Always ask: are the results limited by the scale of measurement of the task? '0' Retention level- possible ceiling effect 9-18 level- floor effect? Solution- run pilot study and adjust scale or task accordingly |
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Interpreting Results Regression Artifacts |
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Interpreting Patterns of Research |
Reliability and Replication Reliability increased when a) large number of observations b) repeatable results Replication results=experimental reliability vs. statistical reliability Three kinds of replication a) direct-repeat experiment as closely as possible b) systematic- repeat experiment while varying factors considered irrelevant c) conceptual-replicate the phenomenon in an entirely different way |
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Interpreting Patterns of Research Converging Operations |
a) e.g., Stroop effect: Increased time to name a color with the ink and color names don't match b) Interpretations: i) Perceptual inhibition- reading inhibits perception ii) Response competition-between two different names that are elicited |
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Which small-n-design is most susceptible to confounding from the order of conditions? |
AB |
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In an ABA design, we can conclude that it was the treatment variable that affected the change during phase B if |
behavior in the third phase did return to the baseline |
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Which of the following is generally agreed to be a characteristic disadvantage of (or threat to validity in) a reversal design |
The possibility of carryover effects |
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Which statement is true of within-subjects multiple baseline experiments? |
Effects cannot be attriubuted to the independent variable if the measured behaviors interact. |
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Which of the following is characteristic of changing-criterion design? |
The researcher manipulates the contingency for a particular outcome. |
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A quasi-experiment differs from a true experiment because in a quasi-experiment |
Researcher selects levels of the independent variable |
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In an interrupted time series design, there are all of the following except |
Interruptions caused by uncontrolled variable other than the treatment |
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The phenomenon of regression to the mean implies that if your parents are slightly more intelligent than the average, your intelligence is probably: |
above average but less than your parents' |
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You are interested in surveying attitudes about gambling as a function of age. Assume that you decide to conduct a poll today about gambling expenditures. This poll will consist of an equal number of people at 18, 24, 30, and 60 years of age. This is an example of which age-related method? |
cross-sectional |
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An interaction between age and an experimental treatment means that: |
The effect of the experimental treatment differed at various ages |
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The issue of scale attenuation in the dependent variable refers to the problems of interpretation when performance is: |
either nearly perfect or very poor |
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Suppose that you were an A student, but on your last test you received a B, and the average of the class was a C. The phenomenon of statistical regression suggests that on your next test you will most likely receive a(n) |
A |
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Experimental reliability may be established by: |
replication with an additional sample of similar participants |
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Systematic replication of an experiment involves: |
changing numerous variables not thought to be critical to the phenomenon under consideration |
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Converging operations are important in psychology because: |
they serve to eliminate alternative explanations of a phenomenon |