Research Designs Internal Validity • Isolation of the independent variable(s) External Validity 1 Randomized designs • Experiments where participants are randomly assigned to the experimental groups or conditions. • Often referred to as “true experiments.” Randomized designs • Provides a safeguard against biased assignment of sampling units to the different treatment groups. • Distributes the characteristics of the sampling units over the different conditions to prevent biased outcomes. • Permits the use of statistical analyses that require certain data characteristics. 2 Ways of achieving random assignment • Presorting booklets or questionnaires • Blindly drawing names • Flipping a coin • Consulting a table of random numbers Non factorial designs (one independent variable: one way): • Between subjects • Within subjects Factorial designs: • Between subjects • Within subjects • Mixed 3 Between subjects designs • Subjects are Condition A Condition B exposed to one condition each. Subject 1 Subject 2 • Also called nested Subject 3 Subject 4 designs. Subject 5 Subject 6 Subject 7 Subject 8 Subject 9 Subject 10 Within subjects designs • Subjects are Condition A Condition B Subject 1 Subject 1 exposed to each Subject 2 Subject 2 condition. Subject 3 Subject 3 – Also called: Subject 4 Subject 4 • Repeated-measures Subject 5 Subject 5 design Subject 6 Subject 6 • Crossed design Subject 7 Subject 7 • Importance of Subject 8 Subject 8 counter-balancing Subject 9 Subject 9 Subject 10 Subject 10 4 Threats to internal validity Between or within subjects designs Threats of internal validity: • Researcher expecta***betweention • Participant expectati***betweenon • Participant selectio***betweenn • Maturation and historical factors • Lost of participa***betweennt • Habituation and fatigue • Statistical regression 5 Threats to internal validity: • Researcher expectan***withincy • Participant expectanc***withiny • Participant selection • Maturation and historical f***withinactors • Lost of participan***withint • Habituation and fatig***withinue • Statistical regressio***withinn Controls: • Constancy • Systematic variation —counter-balancing: Latin Square • Random variation 6 Latin Square Latin Square Order of administration 1 2 3 4 Sequence 1 A B C D Sequence 2 B C D A Sequence 3 C D A B Sequence 4 D A B C 7 Within subject (repeated measures) pre -test – V. I. – post test pre -test – V. I. – post test pre-test post test Solomon design 1. pre-test – I. V. – post test 2. I. V. – post test 3. pre-test – – post test 4. – post test 8 1. pre-test – I. V. – post test Solomon 2. I. V. – post test Design 3. pre-test – – post test 4. – post test Pre-test yes no yes 1 2 I. V. no 3 4 Factorial design: • Between-subject • Within-subject • Mixed 9 What is the research design? 1. Find the independent variables 2. For each I. V.: • Within-subject or between subject? • levels (names & numbers) 2 X 2 mixed design with the independent variables x (within) & y (between) Factorial designs Hypotheses: • Main effects (= number of I. V.) • Interaction 10 Main effects English English French French Males Females Age Sex Interaction English French English French Males Females Age Sex 11 BURNHAM (1966) Expectancy control design Expectancy Brain state Lesioned Unlesioned Totals Lesioned 46.5 49.0 95.5 Unlesioned 48.2 58.3 106.5 Totals 94.7 107.3 I. V.? • Brain state Within- or between-subject ? Levels? 2 Lesioned vs. Not lesioned • Researcher Expectancy Within- or between-subject ? Levels? 2 Lesioned vs. Not lesioned 12 2 X 2 Between-subjects Design Brain state Lesioned Not-Lesioned Belief: Belief: Belief: Belief: lesion No lesion lesion No lesion 13.