The anova summary table extending anova to factorial

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Unformatted text preview: you want to have a lower chance of a Type I error. The ANOVA summary table Extending ANOVA to Factorial designs systematic variance broken up into subparts, for each of the main effects and for the interaction terms Don’t worry about calculation of these You may see a more extensive ANOVA table, e.g. How one would talk about the results? Main effect for A, No main effect for B, Significant interaction. Followup / Post hoc Tests When there are more than two levels of an IV, you don’t know which was the different one. post hoc tests or multiple comparison tests Used AFTER a significant F was found overall. Between vs. Within-subjects ANOVAs Just like before. Within-subject designs are more ‘powerful’ because they minimize error variance Analysis of these requires special consideration (like the paired-t test rather than the std t-test). Multivariate ANOVA or MANOVA Used when more than one DV. Problem is inflation of Type I error when you have multiple DVs you are analyzing. If 5 DVs you have a higher chance of one of them showing up significant. Nonexperimental use of ANOVAs This is fine. Be aware that just because ANOVA is used it doesn’t mean it’s a ‘true experiment’ Assumptions/Robustness normal distributions equal variance between conditions Single-subject research methods Why? What’s the problem with group research? 5 Hides data - summarizing across subjects hides individual performance. The “Average individual” may not be similar to any subject (e.g. 2.1 children). Note, this does not preclude averaging within an individual. Also, average group behavior can answer some questions about how group on the average will perform - you just can’t address individual behavior without further evidence Examples: Simulation study of blocking - backward blocking and forward blocking. Pigeon use of kinematic depth cues Classic learning curve Criticisms of group designs The ‘averaging’ problem just mentioned Error variance includes individual differences (intersubject variance) as well as differences within an individual (intra subject variance). Terms nomothetic (NA-MA-Thetic)- establish general principles and broad generalizations idiographic (ID-E-A-Graphic) - seek to describe, analyze and compare individual subject behavior. Single-subject research Doesn’t imply only a single subject in the study typically from 3 to 8, but analyzed and discussed as individuals. Can use statistics (including inferential!!!) as well as graphical techniques. Typically done under the rubric of Experimental Analysis of Behavior Journal of the Experimental Analysis of Behavior Journal of the Applied Analysis of Behavior Analysis of single-subject data Graphical analysis Statistical analysis EXPERIMENTAL Designs The search for a STABLE baseline is...
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This note was uploaded on 06/30/2012 for the course PSY 211 taught by Professor Chance during the Spring '11 term at University of Phoenix.

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