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32 Cards in this Set

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  • Back
Describe History of Single Subject Reseach
Early psychologists analyzed individual cases, used repetition to establish "true effects of treatments or perceptual phenomena. Approach remained popular until Fisher's inferential statistics (1920's& 1930's), then practiced mainly by Skinner and followers.
Baseline Designs
Establish behavioral baseline (natural rate) in baseline phase, then introduce intervention phase
Behavioral Baseline
record of performance-multiple responses over time within phase.
Stability Criterion
Baseline no longer shows any systematic trends, has stabilized as shown in plot over time.
Intrasubject replication
repeated cycle of baseling and intervention
Step One: Implempenting a single-subject design.
1. Identify and operationally define the behavior to be modified
Step two: Implementing a single-subject design
2. Establish a baseline, e.g. through timesampling
Step three: Implementing a single-subject design
Maintain running plot over time, set stability criterion, wait for stabilit.
Step four: Implementing a single-subject design
Introduce intervention, track results over time
Step five: Implementing a single-subject design
Return to baseline via reversal strategy (e.g. discontinue rewards)
Multiple Baseline Designs
Used when intervention causes irreversible changes- investigator tracks two behaviors, modifies one while the other is left alone
Discrete trials designs
1. Individuals receive each treatment condidtion multiple times, in seperate trials.
2. Extraneous variables are tightling controlled.
3. Order of presentation is randomized or counterbalanced to avoid order effects.
4. Inter-subject replication
Advantages of Single-subject research
1. Small number of participants needed.
2. Focus on controlling extraneous variation may be more successful in identifying.
3. May give truer estimate of impact of independent variable.
4. Can give evidence of causal relationship.
Disadvantages of Single-subject research
1.High level of experimental control needed for success
2. Requirement for long period of time, multiple observations over time.
3. Limited generality-highly artificial environment, few participants.
Field Study shortcommings
1. Only show correlation, and do not imply causation
2. Don't have independent variables, just measeurement.
3. Take place in natural settings, usually not in controlled environments
Causal inference
Concluding that a variable or event has an effect on another variable or event, based on 3 criteria: a)correlation of the supposed cause and effect; b)time sequence in which supported cause precedes effect; and c)fuling out alternative explanantions based on other factors that might account for a correlation.
Between-subjects experiement
Type of experiment in which each participant experiences only one level of the independent variable, and comparison groups consist of different individuals.
Within-subject experiements
Type of experiment in which participants experience all levels of the independent variable, so compariosons among experimental groups involve the same individuals
Randomized two-group experiment with one posttest
Simplest between-subjects design.
a)One independent variable with 2 levels b)Random assignment of individuals to one of two conditions c) Application of the independent variable d)Measurement of the dependent variable afterwards, at just one time
Randomized two-group experiment Advantages
Brief sessions
Fast and inexpensive
Randomized two-group experiment Disadvantages
a)prone to high error variance b)needs large N to find a significant difference
Matched Groups experiement
Experiment that divides participants into groups approximately equal on one extraneous variable, a matching variable correlated with the dependent variable, in four steps
Steps to Matched Groups experiment
a) Measure a matching variable among participants b)rand-order it c)Divide the ranked list into the number of groups d)Randomly split each group among the comparison groups
Pretest-Posttest Design
Experiment or quasi-experiment involving measurement of the dependent variable before treatment and again after treatment.
Repeated Measurement
Collecting data on a measure of one variable for the same individuals on two or more occasions, using exactly the same procedures each time, ideally at equal time intervals
Parametric Experiment
Type of between-subjects experiment in which the independent variable represents continuum and the experiment includes three or more different levels of that factor. (e.g. Study of 5 different glucose dosages on short-term recall).
Factorial Experiment
Type of experiment with more than one independent variable, in which every level of each independent variable appears in comibination with every level of every other independent variable.
Interaction (among variables)
In a factorial experiment, differential impact of one factor on the dependent variable as a function of levels of another factor.
Within-subjects experiment
Type of experiment in which participants experience all levels of independent variable, so comparionsons among experimental groups involve the same individuals
Carryover effects
In a within-subjects experiment, an effect of a previous treatment or previously experienced level of the independent variable on responses to the current treatment, creating an alternative explanantion besides the current treatment for the response to it.
In within-subjects experiement-giving individual particpants the treatments or levels of the independent variable in different sequences so that, for the whole study, every treatment precedes as often as it follows every other treatment.
Latin Square
Series of sequences of different items, comprosing the same number of sequences as items, in which each item precedes as often as it follows every other, used for counterbalancing the treatment conditions in a within-subjects experiment