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Lecture 15

Lecture 15 - Within-group or within-subjects designs.docx

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Department
Psychology
Course
Psychology 2800E
Professor
Doug Hazlewood
Semester
Fall

Description
Within­Group (or “within­subjects”) Designs Prologue: Types of Experimental Designs A. Between-Group (or between-subjects) - Different groups get different conditions of IV. o E.g., 2 levels (or conditions):  Experimental group (subjects 1-10)  Control Group (subjects 11-20) o Or multiple levels (conditions), e.g.,  No treatment group (1-10)  Moderate treatment group (11-20)  High treatment group (21-30) B. Within-group or (within-subjects) - All participants exposed to all levels of IV o Experimental condition (subjects 1-10) o Control condition (same subjects 1-10) - Aka: “repeated-measures” design - Can also have “multiple conditions” if IV has more than 2 levels (all p’s will still be in all conditions) C. “Mixed-factorial” (or “mixed”) design - “factorial”: more than one IV (or “factor”) - “mixed”: 1 IV manipulated within subjects, 1 IV manipulated between groups - See next lecture (and Ch 11) for more on factorial experiments Part 1: Within­Group Designs (Conditions tested once) Example 1: Pretest-treatment-posttest design (aka: “one group pretest-posttest design” p. 263) - Better than: o One group posttest-only design (p.262) o Posttest-only with NE control groups (p.262) - BUT: has many threats to internal validity o Must add a “no treatment” control group  a “mixed” design • Pre vs. post is within subjects • Treatment vs. no treatment is between groups Example 2: Evaluating golf balls (“A” and “B”) - Type of ball is IV (each ball is a “treatment” or “condition”) - DV = distance balls travel - In between-group design, we’d have 2 groups with random assignment: o Group 1 hits ball A, Group 2 hits ball B o With 10 participants in each group, we’d need 20 participants - In within-group design, each participant hits both balls (e.g., A then B), number of participants is 10 Advantages of within-group design - Need fewer participants (e.g., 10 vs. 20) - Controls for variability from individual differences o Can be controlled in between-group designs  Use homogenous participants (e.g., “pro” golfers)  “Match” participants on golfing ability  Match on more things by using identical twins o Best to match person with self!  Removes variability caused by individual differences  Within-group design does this! Results for within-group experiment - Ball A travels 100 yards - Ball B travels 200 yards - Ball B is better? No! o New “confounds” A. Order Effect (Ball A first, Ball B second) - Order is confounded with treatment (ball) o Practice (warm-up) effect:  Hitting A first provided practice; caused B to go further? o Order can also produce “fatigue” effects - Solution 1: o Use a between-group design (but lose advantages of the within-group design) - Solution 2: o Complete Counterbalancing: Present conditions in all possible orders o Within 2 conditions, we have 2 “orders (AB, BA);  Include order as between-group factor (becomes “mixed design”) • But number of possible orders increases with number of conditions: “X!” o 2 conditions: X! = 2 x 1 = 2 o 3 conditions: X! = 3 x 2 x 1 = 6 o 6 conditions: X! = 720 possible orders - Solution 3: o “Partial” Counterbalancing: use a subset of the possible orders o Use a Latin square to control
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