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Chapter 9

by: Takyra Thompson

Chapter 9 Psyc 318

Takyra Thompson
GPA 2.45
Research Methods
Barbara Winstead

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About this Document

Factorial Design
Research Methods
Barbara Winstead
Class Notes
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This 3 page Class Notes was uploaded by Takyra Thompson on Friday October 16, 2015. The Class Notes belongs to Psyc 318 at Old Dominion University taught by Barbara Winstead in Summer 2015. Since its upload, it has received 22 views. For similar materials see Research Methods in Psychlogy at Old Dominion University.


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Date Created: 10/16/15
Chapter9 Factorial Designs 0 90 Factorial Designs two or more independent variablesfactors O FactorvariablesingleIV group variables noneXperimental variables 0 Example 2 IVs 2 group variables 2 IVs and gender 0 Represented by the number of factors by factors I EX 2 X 2 X 2 X 2 2 represents of levels this equals a factorial design This examples has 4 factors I Level means that there are subgroups of a factor 0 Betweensubjects factorial design different participants in each condition 0 Participants in only one condition cannot not be in more than one condition 0 Withinsubjects factorial design participants in each and every condition 0 Each participants eXperience each condition eXperience more than one condition 0 Mixedfactorial designsone or more betweensubjects variables and one or more Withinsubjects variables v Factorial Design 0 Order of variables does not matter 0 Needs at least three levels to examine nonlinear effects in an IV Main EffectIV has significant effect on DV eX overall mean difference Interaction Effecteffect of IV on DV depends on level of another IV Person X Situation Factorial Design 0 One subject variable With one manipulated situational variable I EX gendersubject variable room temperaturemanipulated O O O 90 90 90 situational variable adds up to a 2 X 2 design and a 2 X 3 design 0 Difference between Quasiindependent and true independent variables still holds 0 Effect of the quasiindependent variables are correlational 0 Call quasiindependent variables predictor variables to avoid confusion 393 Main Effect and Interactions O Marginal means re ects average of cell means for the relevant row or column ditions 1 Co 39on 2 Condition 3 Conditi 4 0 Cell M means average of each condition or level 393 Analyzing Results O ANOVAstatistical framework for factorial designs 0 Example A 2 X 2 ANOVA includes three test of statistical significance I Test 1 main effect of Factor A I Test 2 main effect of Factor B I Test 3 A X B interaction 393 Example of a 2 X 2 Anova 0 Implicit theories between ss I 60 Jewish Israeli university students randomly assigned to one of four conditions Implicit Theory Entity vs Incremental 0 Entitypersonality is fixed 0 Incrementalpersonality can change Attribution I dispositionalinstructed to choose dispositional attribution of 7 stereotyped images model with low SAT scores unintelligent situationalinstructed to choose situational attribution for 7 stereotyped images models with low SAT scoresshe received bad news before the test DVendorsement of negative traits of Arabs I Design 0 2 implicit theory entity and incremental X 2attribution dispositional and situational 0 Entity dispositional5 9 O Entity situational43 O Incremental dispositional45 O Incremental situational44 0 Main effects 0 Ss in incremental condition had lower endorsement of negative traits than ss in entity condition 0 Ss in situation attribution condition had lower endorsement of negative traits than ss in dispositional condition 0 Interaction of implicit theory with attribution 0 Significant 393 Analyzing Results 0 Simple main effectseffect of one IV at a particular level of another IV I Use when making sense of interactions 0 Simple contrasts type of posthoc test I Use when statistically significant simple main effects emerge O Priori theorizing drive hypotheses about specific mean difference I Test with planned comparisons Mean difference need not be as large to be statistically significant 393 Post Hoc vs Planned Analyses O O Post Hoc Planned A priori Do not have clear theory driven directional 0 You have a limited number of specific I hypothesis comparisons you want to make Omnibus test ANOVA 0 Just test the comparisons of interest Follow up With comparisons O 393 Three IVs 0 Four possible interaction 393 Example 0 Sex difference in internalizinf problems during adolescence in Autism Spectrum Disorder ASD 0 Three twoway interactions A X B A X C B X C One three way interaction A X B X C 32 adolescence With ASD 32 adolescence Without ASD ASD is comorbid With internalizing problems anXiety and depression Girl are affected more by internalizing problems than boys but evidence on children With ASD is mixed Early adolescence higher risk for internalizing problems but more so for girls 2 ASD vs Type X 2 seX of s X age early 1224 vs late 1517 adolescence 2X2X2x2 Sessions control depletion X Valence of picture neutral negative X Regulation maintain decrease X Order depletion first depletion second Main effects Valencemore startle With negative vs neutral picture Interactions Valence X valence X regulation can regulate With neutral pictures better than With negative pictures Session X valence X regulationsupports hypothesis depletion makes regulation harder in negative picture condition No order effects Startle potentiation negative startleneutral startle


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