1 of 29 Department of Cognitive Science Adv. Experimental Methods & Statistics PSYC 4310 / COGS 6310 Mixed Model ANOVA Michael J. Kalsher PSYC 4310/6310.

Slides:



Advertisements
Similar presentations
Complex Experimental Designs
Advertisements

Cross Sectional Designs
Statistics for the Social Sciences
Analysis of variance (ANOVA)-the General Linear Model (GLM)
SPSS Series 3: Repeated Measures ANOVA and MANOVA
Brooke Bussone Dylan Antovich. The Evolutionary Theory of Romantic Jealousy Jealousy is an adapted function designed to increase fitness Two factors in.
Statistics for the Social Sciences Psychology 340 Fall 2006 Repeated Measures & Mixed Factorial ANOVA.
The Psychologist as Detective, 4e by Smith/Davis © 2007 Pearson Education Chapter Twelve: Designing, Conducting, Analyzing, and Interpreting Experiments.
Method IntroductionResults Discussion Effects of Plans and Workloads on Academic Performance Mark C. Schroeder University of Nebraska – Lincoln College.
Inferential Stats for Two-Group Designs. Inferential Statistics Used to infer conclusions about the population based on data collected from sample Do.
Chapter 10 - Part 1 Factorial Experiments.
Mindfulness and Attachment Style: & The Explanatory Role of Emotion Regulation Crystal Pearce, William Lovegrove, Steven Roodenrys.
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.
Wrap-up and Review Wrap-up and Review PSY440 July 8, 2008.
Statistics for the Social Sciences
Today Concepts underlying inferential statistics
Method Introduction Results Discussion The Effect of Self-Esteem, Marital Status, and Gender on Trait Anxiety and Stress Emily B Gale University of Nebraska-Lincoln.
Psyc 235: Introduction to Statistics
Two-Way Analysis of Variance STAT E-150 Statistical Methods.
1 of 27 PSYC 4310/6310 Advanced Experimental Methods and Statistics © 2013, Michael Kalsher Michael J. Kalsher Department of Cognitive Science Adv. Experimental.
Basic Statistics Michael Hylin. Scientific Method Start w/ a question Gather information and resources (observe) Form hypothesis Perform experiment and.
Implication of Gender and Perception of Self- Competence on Educational Aspiration among Graduates in Taiwan Wan-Chen Hsu and Chia- Hsun Chiang Presenter.
By Hui Bian Office for Faculty Excellence 1. K-group between-subjects MANOVA with SPSS Factorial between-subjects MANOVA with SPSS How to interpret SPSS.
1 of 46 MGMT 6970 PSYCHOMETRICS © 2014, Michael Kalsher Michael J. Kalsher Department of Cognitive Science Inferential Statistics IV: Factorial ANOVA.
Testosterone, Attachment and the green-eyed monster Nicola J. Fussell & Angela C. Rowe School of Experimental Psychology, University of Bristol, UK. Are.
Chapter 10 Experimental Research: One-Way Designs.
Statistics for Education Research Lecture 8 Tests on Three or More Means with Repeated Measures: One-Way ANOVA with Repeated Measures Instructor: Dr. Tung-hsien.
Statistics for the Social Sciences Psychology 340 Spring 2006 Factorial ANOVA.
Gender Differences In Relational Versus Achievement Influences On Self-esteem Rick L. Payne, B.A., B.S. Department of Psychology, University of Dayton.
Psychology 301 Chapters & Differences Between Two Means Introduction to Analysis of Variance Multiple Comparisons.
Problem-Solving Abilities and Feelings of Control: A Work in Progress Emily M. Kaiser, Department of Communication Studies, College of Arts and Sciences.
Test of Independence. The chi squared test statistic and test procedure can also be used to investigate association between 2 categorical variables in.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
By: Deanna Duermit, Mikayla Mowzoon, Jenna Tioseco
Attractive Equals Smart? Perceived Intelligence as a Function of Attractiveness and Gender Abstract Method Procedure Discussion Participants were 38 men.
1 of 65 Inferential Statistics I: The t-test Experimental Methods and Statistics Department of Cognitive Science Michael J. Kalsher.
Education 793 Class Notes Presentation 10 Chi-Square Tests and One-Way ANOVA.
Statistics for the Social Sciences Psychology 340 Fall 2012 Analysis of Variance (ANOVA)
Department of Cognitive Science Michael J. Kalsher Adv. Experimental Methods & Statistics PSYC 4310 / COGS 6310 Regression 1 PSYC 4310/6310 Advanced Experimental.
Educational Research Chapter 13 Inferential Statistics Gay, Mills, and Airasian 10 th Edition.
Mixed-Design ANOVA 5 Nov 2010 CPSY501 Dr. Sean Ho Trinity Western University Please download: treatment5.sav.
ITEC6310 Research Methods in Information Technology Instructor: Prof. Z. Yang Course Website: c6310.htm Office:
Chapter 14 Repeated Measures and Two Factor Analysis of Variance
Sex differences in romantic kissing among college students: An evolutionary perspective Summary by Amber Kika, Nina Dangourian, and Esmeralda Huerta For.
Slide 1 Mixed ANOVA (GLM 5) Chapter 15. Slide 2 Mixed ANOVA Mixed: – 1 or more Independent variable uses the same participants – 1 or more Independent.
Chapter 10 The t Test for Two Independent Samples
Statistics for the Social Sciences Psychology 340 Spring 2010 Introductions & Review of some basic research methods.
Chapter 13 Repeated-Measures and Two-Factor Analysis of Variance
A health magazine recently reported a study in which researchers claimed that iron supplements increased memory and problem-solving abilities in a random.
ONE-WAY BETWEEN-GROUPS ANOVA Psyc 301-SPSS Spring 2014.
 By preschool age, boys and girls show marked differences on a number of emotional, social, and behavioral outcomes (Ruble et al., 2006). Some gender.
Psych 230 Psychological Measurement and Statistics Pedro Wolf November 18, 2009.
Handout Nine: Repeated Measures –Design, Analysis, & Assumptions.
Outline of Today’s Discussion 1.The Chi-Square Test of Independence 2.The Chi-Square Test of Goodness of Fit.
Copyright c 2001 The McGraw-Hill Companies, Inc.1 Chapter 11 Testing for Differences Differences betweens groups or categories of the independent variable.
Handout Eight: Two-Way Between- Subjects Design with Interaction- Assumptions, & Analyses EPSE 592 Experimental Designs and Analysis in Educational Research.
Research Methods and Data Analysis in Psychology Spring 2015 Kyle Stephenson.
Handout Ten: Mixed Design Analysis of Variance EPSE 592 Experimental Designs and Analysis in Educational Research Instructor: Dr. Amery Wu Handout Ten:
© 2006 by The McGraw-Hill Companies, Inc. All rights reserved. 1 Chapter 11 Testing for Differences Differences betweens groups or categories of the independent.
1 of 29 Department of Cognitive Science Adv. Experimental Methods & Statistics PSYC 4310 / COGS 6310 Mixed Model ANOVA Michael J. Kalsher PSYC 4310 Advanced.
Aron, Aron, & Coups, Statistics for the Behavioral and Social Sciences: A Brief Course (3e), © 2005 Prentice Hall Chapter 10 Introduction to the Analysis.
Mixed-Design ANOVA 13 Nov 2009 CPSY501 Dr. Sean Ho Trinity Western University Please download: treatment5.sav.
Scenario Your have been in a long-term relationship for 3 years. You have decided to move in together. Your best friend has just told you that when they.
Oneway ANOVA comparing 3 or more means. Overall Purpose A Oneway ANOVA is used to compare three or more average scores. A Oneway ANOVA is used to compare.
Copyright © 2009 Pearson Education, Inc LEARNING GOAL Interpret and carry out hypothesis tests for independence of variables with data organized.
Chapter 14 Repeated Measures and Two Factor Analysis of Variance PowerPoint Lecture Slides Essentials of Statistics for the Behavioral Sciences Seventh.
Multivariate vs Univariate ANOVA: Assumptions. Outline of Today’s Discussion 1.Within Subject ANOVAs in SPSS 2.Within Subject ANOVAs: Sphericity Post.
Chapter 10 Introduction to the Analysis of Variance
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:

1 of 29 Department of Cognitive Science Adv. Experimental Methods & Statistics PSYC 4310 / COGS 6310 Mixed Model ANOVA Michael J. Kalsher PSYC 4310/6310 Advanced Experimental Methods and Statistics © 2012 Michael Kalsher

2 of 29 Outline Introduction to Mixed Model Designs Lab and practice data sets

3 of 29 Sample Problem An adult attachment researcher reads an article which shows that insecure attachment can exert physiological effects on children, including negatively impacting their quality of sleep. The researcher decides to investigate whether similar effects may occur in married couples. Previous research had indicated that periods of almost any kind of anxiety or stress are also associated with sleep disturbances, such a reduction in deep (delta) sleep. Stressed individuals exhibit a tendency toward less and lighter sleep. The researcher conducts a study to determine whether the presence of a person’s spouse while sleeping reduces the presence of sleep disturbances in individuals who are stressed.

4 of 29 Method Participants. 30 women who had recently moved to a new area to begin new jobs with their spouses. Among the women, 10 are secure, 10 are anxious, and 10 are avoidant in their attachment styles. Procedure. The sleep patterns of the 30 women are monitored while they sleep alone and while they sleep with their spouses. The DV is the overall percentage of time spent in deep delta sleep. Design. Two-way mixed ANOVA with one within-subjects factor and one between-groups factor. Partner-proximity (sleep with spouse vs. sleep alone) is the within-subjects factor; Attachment style is the between-subjects factor. H1: Subjects will experience significantly greater sleep disturbances in the absence of their spouses due to the stressful nature of their present circumstances. H2: Subjects with secure attachment styles will derive comfort from the presence of their spouses and will experience significantly more deep delta sleep than subjects with insecure attachment styles.

5 of 29 Data View Attachment Style Key 1 = Secure 2 = Anxious 3 = Avoidant

6 of 29 Variable View

7 of 29 Step 1 Step 2

8 of 29 Step 3Step 4

9 of 29 Step 5 Why add these two factors? Why not add “Partner”? Step 6

10 of 29

11 of 29 Homogeneity Assessment

12 of 29 Main effect of Partner Partner x Attachment Style Interaction Note: Partner “1” = Sleeping Partner Absent Partner “2” = Sleeping Partner Present Main Analyses: Repeated Measures

13 of 29 Can you find the source of the interaction? SecureAnxiousAvoidant AttachStyle Partner Absent Partner Present Percent Time in Delta Sleep

14 of

15 of 29 Critical Values for F

16 of 29 The statistics instructor at a local college is interested in examining whether students’ scores on their stats exams are influenced systematically by the time of testing, the course instructor (there were three different instructors), or whether the course is required (some crazy students in other majors opt to take the course!). Students took a pre-test at the beginning of the term, a midterm and a final. Which procedures will you use to analyze the data? What is/are the Independent Variable(s)? Dependent Variable? What are the results? Mixed Model ANOVA: Sample Problem

17 of 29 SubjectPretestMidtermFinalInstructRequired

18 of 29 Mixed-Model ANOVA: Variable View

19 of 29 Mixed-Model ANOVA: Data View

20 of 29

21 of 29

22 of 29 Descriptive Statistics: what’s going on?

23 of 29 Main Analyses: Repeated-measures

24 of 29 Post-hoc Tests: Decomposing the Main Effect of Time-of-Test

25 of 29 Post-hoc Tests: Decomposing the Instructor x Time-of-test Interaction

26 of 29 Post-hoc Tests: Decomposing the Instructor x Time-of-test Interaction

27 of 29 Main Analysis: Between-Subjects Variables

28 of 29 Writing up the Results Mauchly’s test indicated that the sphericity assumption was violated for the main effect of Time-of-test,  2 (2)=14.96, p<.01. Therefore, degrees of freedom were corrected using Huynh-Feldt estimates of sphericity ( ε =.85). There was a significant main effect of Time-of-testing, F(1.69,25.40)=868.21, p<.01, partial eta-squared =.98. Test scores increased consecutively from the pre-test (M=63.14, SE=2.04) to the Midterm (M=78.4, SE=2.38) to the Final exam (M=85.96, SE=1.99). Post-hoc tests using the Bonferroni procedure revealed significant differences between all three times of testing, p’s<.01. The large effect size estimate suggests the observed increases in test performance over time were substantial. There was also a significant interaction effect between Time-of-testing and Instructor, F(3.39,25.40)=62.37, p<.01, partial eta-squared =.89. As shown in Figure 1, the difference in exam scores among the three instructors was greater for the Final Exam than for either the Pretest or the Midterm.

29 of 29 Figure 1. The difference in student test performance among the three instructors was significantly greater for the Final exam than for the Pretest or Midterm.

30 of 29 Sample Problem An evolutionary view of jealousy suggests that men and women have evolved distinctive types of jealousy because male and female reproductive success is threatened by different types of infidelity. - A woman’s sexual infidelity deprives her mate of a reproductive opportunity and in some cases burdens him with years investing in a child that is not his. - A man’s sexual infidelity does not burden his mate with unrelated children, but may divert his resources from his mate’s progeny This diversion of resources is signaled by emotional attachment to another female.

31 of 29 Jealousy Mechanisms: Men vs. Women Men: Evolved to prevent his mate’s sexual infidelity. Women: Evolved to prevent her mate’s emotional infidelity. Hypothesis - Men and women should divert their attentional resources toward different cues to infidelity, such that: - Women should be on the lookout for emotional infidelity - Men should be on the lookout for sexual infidelity

32 of 29 Schutzwohl 2008 Study Men and women saw sentences on a computer screen. On each trial, participants saw a target sentence that was emotionally neutral (“The gas station is at the other side of the street”). Before each of the neutral targets, a distractor sentence was presented that was either affectively neutral or indicated sexual infidelity. If the distractor sentences grab a person’s attention then they would remember them and they would not remember the target sentence that follows. Further, these effects should show up only in people currently in a relationship.

33 of 29 IVs and DVs IVs: Relationship: The person has a partner or does not. Type of Distractor: Neutral distractor vs. Emotional Infidelity distractor vs. Sexual Infidelity distractor Whether the sentence was a distractor or the target following the distractor DV: Number of Sentences the person could remember.