11. Experimental Research: Factorial Design What are factorial experimental designs, and what advantages do they have over one-way experiments? What is.

Slides:



Advertisements
Similar presentations
Guidelines for IDing Experimental Design Levels/ participant? One Independent Groups design More than one Repeated Measures design Once: incomplete Yes:
Advertisements

Complex Experimental Designs
Anthony Greene1 Advanced ANOVA 2-Way ANOVA Complex Factorial Designs I.The Factorial Design II.Partitioning The Variance For Multiple Effects III.Independent.
FACTORIAL ANOVA Overview of Factorial ANOVA Factorial Designs Types of Effects Assumptions Analyzing the Variance Regression Equation Fixed and Random.
FACTORIAL ANOVA. Overview of Factorial ANOVA Factorial Designs Types of Effects Assumptions Analyzing the Variance Regression Equation Fixed and Random.
Factorial Designs Passer Chapter 9
Issues in factorial design
Chapter Fourteen The Two-Way Analysis of Variance.
Chapter 9 – Factorial Designs Factorial Design -- definition –Two or more IVs –every level of one IV combined with every level of other IV –IVs -- called.
Statistics for the Behavioral Sciences Two-Way Between-Groups ANOVA
PSY 307 – Statistics for the Behavioral Sciences
Dr George Sandamas Room TG60
FACTORIAL ANOVA.
One-Way Between Subjects ANOVA. Overview Purpose How is the Variance Analyzed? Assumptions Effect Size.
Factorial ANOVA 2-Way ANOVA, 3-Way ANOVA, etc.. Factorial ANOVA One-Way ANOVA = ANOVA with one IV with 1+ levels and one DV One-Way ANOVA = ANOVA with.
Lecture 16 Psyc 300A. What a Factorial Design Tells You Main effect: The effect of an IV on the DV, ignoring all other factors in the study. (Compare.
2x2 ANOVA BG & MG Models Kinds of Factorial Designs ANOVA for BG, MG & WG designs Causal Interpretation of Factorial Results.
Chi-Square and F Distributions Chapter 11 Understandable Statistics Ninth Edition By Brase and Brase Prepared by Yixun Shi Bloomsburg University of Pennsylvania.
Complex Design. Two group Designs One independent variable with 2 levels: – IV: color of walls Two levels: white walls vs. baby blue – DV: anxiety White.
Intro to Statistics for the Behavioral Sciences PSYC 1900
Factorial Designs More than one Independent Variable: Each IV is referred to as a Factor All Levels of Each IV represented in the Other IV.
Intro to Statistics for the Behavioral Sciences PSYC 1900 Lecture 14: Factorial ANOVA.
Lecture 13: Factorial ANOVA 1 Laura McAvinue School of Psychology Trinity College Dublin.
2-Way ANOVA, 3-Way ANOVA, etc.
2x2 BG Factorial Designs Definition and advantage of factorial research designs 5 terms necessary to understand factorial designs 5 patterns of factorial.
Experimental Group Designs
Understanding the Two-Way Analysis of Variance
ANOVA: Factorial Designs. Experimental Design Choosing the appropriate statistic or design involves an understanding of  The number of independent variables.
ANOVA Chapter 12.
Part IV Significantly Different: Using Inferential Statistics
Statistical Techniques I EXST7005 Factorial Treatments & Interactions.
Two Way ANOVAs Factorial Designs. Factors Same thing as Independent variables. Referred to as factors when there are more than one in a study. Factorial.
Chapter 10 Experimental Research: One-Way Designs.
Comparing Several Means: One-way ANOVA Lesson 15.
Analysis of Variance (Two Factors). Two Factor Analysis of Variance Main effect The effect of a single factor when any other factor is ignored. Example.
PSY 2005 Week 10 – Simple Effects. Factorial Analysis of Variance Simple Effects.
Chapter 7 Experimental Design: Independent Groups Design.
Factorial ANOVAs.  Factorial Analysis of Variance (ANOVA)  Allows you to enter multiple predictors and parcel out the variance in the outcome due to.
Slide 1 Two-Way Independent ANOVA (GLM 3) Prof. Andy Field.
Two-Way Between Groups ANOVA Chapter 14. Two-Way ANOVAs >Are used to evaluate effects of more than one IV on a DV >Can determine individual and combined.
Business Statistics: Contemporary Decision Making, 3e, by Black. © 2001 South-Western/Thomson Learning 11-1 Business Statistics, 3e by Ken Black Chapter.
Review of Results From data analysis to presentation.
Week of April 20 1.Experiments with unequal sample sizes 2.Analysis of unequal sample sizes: ANOVA approach 3.Analysis of unequal sample sizes: MRC approach.
Statistics for Everyone Workshop Fall 2010 Part 4B Two-Way Analysis of Variance: Examining the Individual and Joint Effects of 2 Independent Variables.
Assignment 1 February 15, 2008Slides by Mark Hancock.
10 Experimental Research: One-Way Designs What types of evidence allow us to conclude that one variable causes another variable? How do experimental research.
Mixed ANOVA Models combining between and within. Mixed ANOVA models We have examined One-way and Factorial designs that use: We have examined One-way.
More sophisticated ANOVA applications Repeated measures and factorial PSY SP2003.
Smith/Davis (c) 2005 Prentice Hall Chapter Fifteen Inferential Tests of Significance III: Analyzing and Interpreting Experiments with Multiple Independent.
Handout Eight: Two-Way Between- Subjects Design with Interaction- Assumptions, & Analyses EPSE 592 Experimental Designs and Analysis in Educational Research.
ANOVA Overview of Major Designs. Between or Within Subjects Between-subjects (completely randomized) designs –Subjects are nested within treatment conditions.
Making Inferences about Causality In general, children who watch violent television programs tend to behave more aggressively toward their peers and siblings.
Chapter 9 Two-way between-groups ANOVA Psyc301- Spring 2013 SPSS Session TA: Ezgi Aytürk.
Two-Way Between Groups ANOVA Chapter 14. Two-Way ANOVAs Are used to evaluate effects of more than one IV on a DV Can determine individual and combined.
Test the Main effect of A Not sign Sign. Conduct Planned comparisons One-way between-subjects designs Report that the main effect of A was not significant.
Two-Way Independent ANOVA (GLM 3)
Chapter 10: Complex Experimental Designs
Factorial Experiments
Experimental Research Designs
Multiple Causes of Behavior
How to Interpret a 2-Way ANOVA
Two Way ANOVAs Factorial Designs.
11. Experimental Research: Factorial Design
Interactions & Simple Effects finding the differences
Complex Experimental Designs
How to Interpret a 2-Way ANOVA
Review Compare one sample to another value One sample t-test
Main Effects and Interaction Effects
Complex Experimental Designs
Factorial Designs Factorial design: a research design that includes two or more factors (Independent Variables) A two-factor design has two IVs. Example:
Presentation transcript:

11. Experimental Research: Factorial Design What are factorial experimental designs, and what advantages do they have over one-way experiments? What is meant by crossing the factors in a factorial design? What are main effects, interactions, and simple effects? What are some of the possible patterns that interaction can take? How are the data from a factorial design presented in the research reports? What is a mixed factorial design? What is the purpose of comparing means, and what statistical techniques are used to do this?

Factorial Experimental Designs Experimental designs with more than one independent variable. The term factor refer to each of manipulated independent variables. Example. IV. Sex (male, female), Ethnicity (Black, White, Asian, Latino) DV. Self-esteem MFMF Black White Asian Ratino 4 levels 2 levels Cells 2  4 designs 2 Factors

The Two-Way Design Example. Violent cartoons and children’s frustrated state increase their aggressive behavior. IV: Violent Cartoons vs. Nonviolent Cartoons Frustrated State vs. Non Frustrated State DV: Children’s aggressive behaviors. Frustrated Not frustrated Violent Nonviolent M = 2.68 N= 10M = 3.25 N= 10 M = 5.62 N= 10M = 2.17 N= 10 Av. M = 4.15 Av. M = 2.71 Av. M = 2.97 Av. M = 3.90

Main Effects, Interactions, and Simple Effects Frustrated Not frustrated Violent Nonviolent M = 2.68 N= 10M = 3.25 N= 10 M = 5.62 N= 10M = 2.17 N= 10 Av. M = 4.15 Av. M = 2.71 Av. M = 2.97 Av. M = 3.90 Main Effects Interactions Simple Effects The effect of each factors The effects in which the influence of one factor on the DV is different at different levels of another factors. The effect of one factor within a level of another factor

ANOVA Summary Table Source Sum of df Mean F p-value Squares Square DV: Aggressive Play Cartoon * Prior State Cartoon by Prior State * Residual Total

Chart Residual Cartoon Prior State C & PS

Understanding Interactions DV Frustrated Nonfrustrated Violent Nonviolent Patterns with Main Effects Only DV Violent Nonviolent

Understanding Interactions DV Frustrated Nonfrustrated Violent Nonviolent Patterns with Main Effects & Interaction Only DV Violent Nonviolent Crossover Interaction

Interpretation and Presentation of Main Effects and Interpretations 2 (cartoon)  2 (prior state) ANOVA was conducted. The results indicated that there were significant main effect of cartoon, F (1, 38) = 4.45, p <.05. Children who viewed the violent cartoon (M = 2.89) were rated as playing more aggressively than children who had viewed the nonviolent cartoon (M = 1.52). This main effect, however, should be qualified by the interaction with prior state, F (1, 36) = 4.42, p <.05. Children who were frustrated and viewed the violent cartoon (M = 5.55) were rated as playing more aggressively than children in other conditions (M = 1.11, 1.48, 1.54, respectively).