Copyright © Allyn & Bacon (2010) Correlated-Groups and Single-Subject Designs Graziano and Raulin Research Methods: Chapter 11 This multimedia product and its contents are protected under copyright law. The following are prohibited by law: (1) Any public performance or display, including transmission of any image over a network; (2) Preparation of any derivative work, including the extraction, in whole or in part, of any images; (3) Any rental, lease, or lending of the program.

Copyright © Allyn & Bacon (2010) Correlated-Groups Designs Introduces a correlation between groups in the way groups are formed Introduces a correlation between groups in the way groups are formed –Within-subjects design: Same participants in each group Same participants in each group –Matched-groups design Uses matched random assignment Uses matched random assignment More sensitive than independent- groups designs More sensitive than independent- groups designs

Copyright © Allyn & Bacon (2010) Within-Subjects Designs All participants are exposed to all experimental conditions All participants are exposed to all experimental conditions Need to control for sequence effects Need to control for sequence effects –The experience with one condition affecting performance in subsequent conditions –Controlled by varying the order of presentation (counterbalancing)

Sequence Effects SOURCES SOURCES –Positive Practice Effects (PPE) –Negative Practice Effects (NPE) –Carryover Effects CONTROLS CONTROLS –Control PPE with prior training –Control NPE with rest intervals –Control carryover effects by varying the order of conditions Copyright © Allyn & Bacon (2010)

Target Search Study Hypothetical Study Hypothetical Study –Within-subjects design –Six participants; order counterbalanced –Three conditions 10 distracters 10 distracters 15 distracters 15 distracters 20 distracters 20 distracters Design on next slide Design on next slide Data on the following slide Data on the following slide

Copyright © Allyn & Bacon (2010) Within-Subjects Design Example

Copyright © Allyn & Bacon (2010) Target Search Study Conditions A (10) B (15) C (20) ParticipantOrder 1ABC ACB BAC BCA CAB CBA Mean Scores

Copyright © Allyn & Bacon (2010) Graph of Results The graph shows how the mean search time increases as the number of distracter items increases The graph shows how the mean search time increases as the number of distracter items increases

Copyright © Allyn & Bacon (2010) Statistical Analysis Appropriate Statistical Analyses Appropriate Statistical Analyses –Correlated t-test (for 2 groups only) –Repeated measures ANOVA Order data so that each line represents one participant and each column represents one condition Order data so that each line represents one participant and each column represents one condition –Note that the columns represent conditions, NOT the order of testing

Copyright © Allyn & Bacon (2010) ANOVA Summary Table SourcedfSSMSFp Between <0.01 Subjects Error

Copyright © Allyn & Bacon (2010) Within-Subjects Strengths More sensitive to small group differences More sensitive to small group differences –The variability due to individual differences is statistically eliminated Fewer participants are needed Fewer participants are needed –Each participant appears in each condition Instructions may take less time Instructions may take less time –Participants were already instructed on the task in previous conditions

Copyright © Allyn & Bacon (2010) Within-Subjects Weaknesses Because participants experience all conditions, they may figure out the hypothesis (potential subject effects) Because participants experience all conditions, they may figure out the hypothesis (potential subject effects) Major issue is sequence effects Major issue is sequence effects –Practice and carry-over effects –Controlled by varying the order of presentation Counterbalancing Counterbalancing Random order of presentation Random order of presentation Latin square design Latin square design

Copyright © Allyn & Bacon (2010) Matched-Subjects Designs Introduces correlation through matched random assignment Introduces correlation through matched random assignment Should match on relevant variables Should match on relevant variables –Variables that affect the dependent variable –Variables that show considerable natural variation in the population sampled

Copyright © Allyn & Bacon (2010) Matching Participants Match participants in sets Match participants in sets –Set size is equal to the number of conditions Matching gets more difficult as: Matching gets more difficult as: –The number of matching variables increases –Matching is done on continuous variables –The number of conditions increase Once sets are matched, randomly assign participants in the set to the conditions Once sets are matched, randomly assign participants in the set to the conditions

Copyright © Allyn & Bacon (2010) Statistical Analysis Analyze as if it were a within-subjects study Analyze as if it were a within-subjects study –Data from matched participants are organized as if the data came from a single participant Act as if the number of participants was equal to the actual number of participants divided by the number of conditions (e.g., for 40 participants and 4 conditions, tell the program that you had 10 participants and 4 conditions in a within- subjects design) Act as if the number of participants was equal to the actual number of participants divided by the number of conditions (e.g., for 40 participants and 4 conditions, tell the program that you had 10 participants and 4 conditions in a within- subjects design)

Copyright © Allyn & Bacon (2010) Strengths and Weaknesses Strengths Strengths –Increased sensitivity to group differences –No sequence effects Weaknesses Weaknesses –Extra work of matching participants –Participants without appropriate matches cannot be used in the study

Copyright © Allyn & Bacon (2010) Single-Subject Designs Extensions of within-subjects designs Extensions of within-subjects designs Single participant tested under all conditions, with the researcher actively manipulating the independent variable Single participant tested under all conditions, with the researcher actively manipulating the independent variable Variation on time-series designs, with repeated measurement of the dependent variable Variation on time-series designs, with repeated measurement of the dependent variable

Copyright © Allyn & Bacon (2010) History of these Designs Intensive studies of individuals was common before R. A. Fisher Intensive studies of individuals was common before R. A. Fisher Fishers development of ANOVA changed the focus of psychology to comparing groups of individuals Fishers development of ANOVA changed the focus of psychology to comparing groups of individuals Skinner was one of the few psychologists who advocated the intensive study of individuals Skinner was one of the few psychologists who advocated the intensive study of individuals

Copyright © Allyn & Bacon (2010) Logic of these Designs Includes independent variable manipulation Includes independent variable manipulation Expect dependent variable response Expect dependent variable response –Note that the response must occur shortly after the manipulation unless there is a theoretical reason to expect a delay Multiple measures before and after the manipulation to identify normal variation and rule out regression to the mean Multiple measures before and after the manipulation to identify normal variation and rule out regression to the mean

Copyright © Allyn & Bacon (2010) Single-Subject Designs Basic Single-Subject design includes Basic Single-Subject design includes –Baseline period –A treatment phase –A post-treatment evaluation period

Copyright © Allyn & Bacon (2010) Types of Designs ABA Reversal Design ABA Reversal Design Multiple Baseline Design Multiple Baseline Design Single-Subject, Randomized, Time- Series Design Single-Subject, Randomized, Time- Series Design

Copyright © Allyn & Bacon (2010) Reversal Design LOGIC LOGIC –Apply, then remove, independent variable manipulation –If change occurs at both application and removal, it suggests a causal connection PROCEDURES PROCEDURES –Baseline measures (Condition A) –Treatment application (Condition B) –Return to baseline (Condition A again) –Additional reversals can be included

Copyright © Allyn & Bacon (2010) Reversal Design Example Reversal conditions Reversal conditions –Condition A: attending to self-stimulation –Condition B: withdrawing attention when self-stimulation occurs Hypothetical results (next slide) suggests that attention does influence self-stimulation Hypothetical results (next slide) suggests that attention does influence self-stimulation Ethics requires return to Condition B Ethics requires return to Condition B

Copyright © Allyn & Bacon (2010) Published Example DeLeon et al. (1997)

Copyright © Allyn & Bacon (2010) Multiple Baseline Design LOGIC LOGIC –Show the effect of the independent variable on several dependent variables –Use when Reversals are undesirable Reversals are undesirable Behavioral changes would not reverse Behavioral changes would not reverse PROCEDURES PROCEDURES –Baseline –Manipulation focused on first dependent variable –Manipulation focused on second dependent variable –…and so on

Copyright © Allyn & Bacon (2010) Multiple Baseline Design

Copyright © Allyn & Bacon (2010) Variations on Multiple Baseline Design Across Behaviors Across Behaviors –Testing effects on different behaviors Across Individuals Across Individuals –Testing effects on different people Across Settings and Time Across Settings and Time –Testing effects in different settings or at different times

Copyright © Allyn & Bacon (2010) Single-Subject, Randomized Time-Series Design LOGIC LOGIC –Repeated measures of the dependent variable interrupted by a randomly placed intervention –If change occurs at the point of intervention, it suggests a causal connection PROCEDURES PROCEDURES –Select minimum baseline and follow- up periods –Randomly select the point of intervention –Compare pattern of scores before and after the intervention

Copyright © Allyn & Bacon (2010) Single-Subject, Randomized Time-Series Design

Copyright © Allyn & Bacon (2010) Replicating Single- Subject Experiments Direct replication Direct replication –Repeating study on the same target behavior Systematic replication Systematic replication –Evaluate procedures across subjects, settings, and/or target behaviors Clinical replication Clinical replication –Combining procedures into a treatment package

Ethical Principles Ethics in treatment studies Ethics in treatment studies –First, do no harm –Second, try to do some good Therefore Therefore –Researcher is ethically bound to leave participants in the best situation, which often means returning to treatment in the reversal design Copyright © Allyn & Bacon (2010)

Summary Can introduce a correlation in two ways Can introduce a correlation in two ways –Within-subjects and matched-subjects designs These designs are more sensitive to small differences between groups These designs are more sensitive to small differences between groups The costs for the greater sensitivity are: The costs for the greater sensitivity are: –Sequence effects (within-subjects design) –Matching difficulties (matched-subjects design) Single-subject designs allow the experimental manipulation of variables Single-subject designs allow the experimental manipulation of variables