Factorial Hypotheses Some review & practice Identifying main effect and interaction RH: Explicit factorial RH: “Blending” interaction and main effect RH:

Slides:



Advertisements
Similar presentations
Complex Experimental Designs
Advertisements

Survey of Major Correlational Models/Questions Still the first & most important is picking the correct model… Simple correlation questions simple correlation.
Factorial Designs Passer Chapter 9
Kxk BG Factorial Designs expanding the 2x2 design reasons for larger designs statistical analysis of kxk BG factorial designs using LSD for kxk factorial.
Topic 12 – Further Topics in ANOVA
Research Methods in Psychology Complex Designs.  Experiments that involve two or more independent variables studies simultaneously at least one dependent.
3-way Factorial Designs Expanding factorial designs Effects in a 3-way design Causal Interpretations of 3-way factorial effects Defining a 3-way interaction.
Confidence Intervals, Effect Size and Power
Pearson’s X 2 Correlation vs. X² (which, when & why) Qualitative/Categorical and Quantitative Variables Contingency Tables for 2 Categorical Variables.
FACTORIAL DESIGNS F Terms for Factorials F Types of Factorial Designs F Notation for Factorials F Types of Effects F Looking at Tables of Means F Looking.
Multiple Group X² Designs & Follow-up Analyses X² for multiple condition designs Pairwise comparisons & RH Testing Alpha inflation Effect sizes for k-group.
Factorial Designs: Research Hypotheses & Describing Results Research Hypotheses of Factorial Designs Inspecting tables to describe factorial data patterns.
Multiple Group X² Designs & Follow-up Analyses X² for multiple condition designs Pairwise comparisons & RH Testing Alpha inflation Effect sizes for k-group.
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.
Describing Factorial Effects Kinds of means & kinds of effects Inspecting tables to describe factorial data patterns Inspecting line graphs to describe.
Meta Analysis & Programmatic Research Re-introduction to Programmatic research Importance of literature reviews Meta Analysis – the quantitative contribution.
Statistical Analysis of Factorial Designs z Review of Interactions z Kinds of Factorial Designs z Causal Interpretability of Factorial Designs z The F-tests.
Multivariate Analyses & Programmatic Research Re-introduction to Programmatic research Factorial designs  “It Depends” Examples of Factorial Designs Selecting.
3-way Factorial Designs Expanding factorial designs Effects in a 3-way design Defining a 3-way interaction BG & WG comparisons Experimental & Non-experimental.
Multivariate Analyses & Programmatic Research Re-introduction to Multivariate research Re-introduction to Programmatic research Factorial designs  “It.
Introduction to Multivariate Research & Factorial Designs
2x2 ANOVA BG & MG Models Kinds of Factorial Designs ANOVA for BG, MG & WG designs Causal Interpretation of Factorial Results.
Multivariate Analyses & Programmatic Research Re-introduction to Multivariate research Re-introduction to Programmatic research Factorial designs  “It.
Some Details about Bivariate Stats Tests Conceptualizing the four stats tests Conceptualizing NHST, critical values and p-values NHST and Testing RH: Distinguishing.
Review of Factorial Designs 5 terms necessary to understand factorial designs 5 patterns of factorial results for a 2x2 factorial designs Descriptive &
Design Conditions & Variables Limitations of 2-group designs “Kinds” of Treatment & Control conditions Kinds of Causal Hypotheses Explicating Design Variables.
Intro to Statistics for the Behavioral Sciences PSYC 1900
Lecture 13: Factorial ANOVA 1 Laura McAvinue School of Psychology Trinity College Dublin.
Multiple-Group Research Designs Limitations of 2-group designs “Kinds” of Treatment & Control conditions Kinds of Causal Hypotheses k-group ANOVA & Pairwise.
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.
Analysis of Factorial Designs Statistical Analysis of 2x2 Designs Statistical Analysis of kxk Designs.
Statistics for the Social Sciences Psychology 340 Fall 2013 Tuesday, November 19 Chi-Squared Test of Independence.
WG ANOVA Analysis of Variance for Within- groups or Repeated measures Between Groups and Within-Groups ANOVA WG ANOVA & WG t-tests When to use each Similarities.
1 GE5 Lecture 6 rules of engagement no computer or no power → no lesson no SPSS → no lesson no homework done → no lesson.
Factorial Design Two Way ANOVAs
Lecture 14: Factorial ANOVA Practice Laura McAvinue School of Psychology Trinity College Dublin.
PSY 250 Exam 3 Review. RESEARCH STRATEGIES  Experimental strategies are not determined solely by potential weaknesses – EVERY study has some weakness.
Role of Research The OOPS Survey and Types of Educational Research.
Types of validity we will study for the Next Exam... internal validity -- causal interpretability external validity -- generalizability statistical conclusion.
Chapter 7 Experimental Design: Independent Groups Design.
Designs. Single-factor designs: Between-subjects.
1 Psych 5500/6500 t Test for Two Independent Means Fall, 2008.
Describing Factorial Effects Kinds of means & kinds of effects Inspecting tables to describe factorial data patterns Inspecting line graphs to describe.
Reintroduction to Factorial Designs (re-)Introduction to factorial designs 5 patterns of factorial results Understanding main effects Research Hypotheses.
Intro to Factorial Designs The importance of “conditional” & non-additive effects The structure, variables and effects of a factorial design 5 terms necessary.
Regression Models w/ 2 Categorical Variables Sources of data for this model Variations of this model Definition and advantage of factorial research designs.
Intermediate Applied Statistics STAT 460 Lecture 17, 11/10/2004 Instructor: Aleksandra (Seša) Slavković TA: Wang Yu
Basic Analysis of Factorial Designs The F-tests of a Factorial ANOVA Using LSD to describe the pattern of an interaction.
Sampling and Probability Chapter 5. Sampling & Elections >Problems with predicting elections: Sample sizes are too small Samples are biased (also tied.
Describing Relationships Using Correlations. 2 More Statistical Notation Correlational analysis requires scores from two variables. X stands for the scores.
Presenter: Han, Yi-Ti Adviser: Chen, Ming-Puu Date: March 02, 2009 Papastergiou, M.(2009). Digital Game-Based Learning in high school Computer Science.
Factorial Designs: Programmatic Research, RH: Testing & Causal Inference Applications of Factorial designs in Programmatic Research Research Hypotheses.
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.
Two-Way (Independent) ANOVA. PSYC 6130A, PROF. J. ELDER 2 Two-Way ANOVA “Two-Way” means groups are defined by 2 independent variables. These IVs are typically.
Introduction to “Kinds” of 2-way Factorial Designs Incorporating within-groups comparisons ANOVA for BG, MG & WG designs Applying LSD mmd to kxk designs.
Kxkxk 3-way Factorial Designs kxkxk 3-way designs, effects & causality 3-way interactions describing effects and checking if they are. “descriptive” or.
Other Ways of Thinking About Interactions Ways of Describing Interactions other than “Simple Effects” Interactions as “other kinds of” cell mean difference.
3-way Designs defining 2-way & 3-way interactions all the effects conditional and unconditional effects orthogonality, collinearity & the like kxkxk kxkxq.
8 Experimental Research Design.
Experiment Basics: Designs
Multiple Causes of Behavior
Data, Univariate Statistics & Statistical Inference
Do Now What are the pros and cons of using a case study as a means to gather information for describing behavior.
Analysis of Complex Designs
Experiment Basics: Designs
Experiment Basics: 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:

Factorial Hypotheses Some review & practice Identifying main effect and interaction RH: Explicit factorial RH: “Blending” interaction and main effect RH: Implied RH: involved in programmatic research

Review #1-- interaction Task Presentation Paper Computer Task Difficulty Easy Hard ) Put in a or = to indicate the pattern of the simple effect of Task Presentation for Easy Tasks 2) Put in a or = to indicate the pattern of the simple effect of Task Presentation for Hard Tasks 3) Is there an interaction? Is the simple effect of Task Presentation the same for Easy and for Hard Tasks ??? 4) Write-up the pattern of the interaction... > < No! There is an interaction of Task Difficulty and Task Presentation, as they relate to performance. Paper presentation works better than Computer presentation for Easy tasks, however Computer presentation works better than Paper presentation for Hard tasks.

Review #1-- 1st main effects Task Presentation Paper Computer Task Difficulty Easy Hard ) Compute the marginal means for Task Presentation. 3) Is there a main effect of Task Presentation ??? 4) Is the pattern of the main effect of Task Presentation descriptive or potentially misleading (is the pattern of the main effect of Task Presentation the same as the patterns of the simple main effects of Task Presentations for Easy and Hard Tasks ? 2) Put in a or = to indicate the pattern of the main effect of Task Presentation 5) Write-up the main effect = Nope! Potentially misleading There is no main effect of Task Presentation, however this is misleading, because there are simple effects of Task Presentation for each level of Task Difficulty

Review #1-- 2nd main effects Task Presentation Paper Computer Task Difficulty Easy Hard ) Compute the marginal means for Task Difficulty 3) Is there a main effect of Task Difficulty ??? 4) Is the pattern of the main effect of Task Difficulty descriptive or potentially misleading (is the pattern of the main effect of Task Difficulty the same as the patterns of the simple main effects of Task Difficulty for Computer and Paper Presentations ? 2) Put in a or = to indicate the pattern of the main effect of Task Difficulty 5) Write-up the main effect > Yep! Descriptive – same pattern for both There is a main effect for Task Difficulty. Overall, participants performed better on the Easy tasks.

RH: for Factorial Designs Research hypotheses for factorial designs may include RH: for main effects involve the effects of one IV, while ignoring the other IV tested by comparing the appropriate marginal means RH: for interactions usually expressed as “different differences” -- differences between a set of simple effects tested by comparing the results of the appropriate set of simple effects That’s the hard part -- determining which set of simple effects gives the most direct test of the interaction RH:

Is each an Interaction or a Main Effects RH:??? (Hint – read them in pairs!) Males tend to outperform females on standardized math tests. Males tend to outperform females on standardized math tests, however the difference decreases with age. ME INT Improvement during therapy for depression occurs faster for those receiving cognitive-behavioral therapy than for those receiving traditional psychodynamic therapy. Therapy for depression is generally effective. INT ME Young girls and boys have similar overall skill levels. Young girls have better verbal skills than motor skills, however young boys have better motor skills than verbal skills. ME INT

Sometimes the Interaction RH: is explicitly stated when that happens, one set of SEs will provide a direct test of the RH: (the other won’t) This is most directly tested by inspecting the simple effect of paper vs. computer presentation for easy tasks, and comparing it to the simple effect of paper vs. computer for hard tasks. Here’s an example: Easy tasks will be performed equally well using paper or computer presentation, however, hard tasks will be performed better using computer presentation than paper. Presentation Comp Paper Task Diff. Easy Hard = >

Young boys will rate playing with an electronic toy higher than playing with a puzzle, whereas young girls will have no difference in ratings given to the two types of toys. (DV = toy rating) Type of Toy Elec. Puzzle Gender Boys Girls = > Judges will rate confessions as more useful than eyewitness testimony, whereas Lawyers will rate eyewitness testimony as more useful than confessions. (DV = usefulness rating) Type of Evidence Confession Witness Rater Judge Lawyer <> Your Turn – “Draw the boxes” & use or = to depict the interaction. Tell which set of SEs you will use! SE of Toy for each gender SE of Type of Evidence for each Rater

Sometimes the set of SEs to use is “inferred”... Often one of the IVs in the study was used in previous research, and the other is “new”. In this case, we will usually examine the simple effect of the “old” variable, at each level of the “new” variable this approach gives us a clear picture of the replication and generalization of the “old” IV’s effect. e.g., Previously I demonstrated that computer presentations lead to better learning of statistical designs than does using a conventional lecture. I would like to know if the same is true for teaching writing. Let’s take this “apart” to determine which set of SEs to use to examine the pattern of the interaction...

Previously I demonstrated that computer presentations lead to better learning of statistical designs than does using a conventional lecture. I would like to know if the same is true for teaching writing. Here’s the design and result of the earlier study about learning stats. Type of Instruction Comp Lecture > Here’s the design of the study being planned. Type of Instruction Comp Lecture Topic Stats Writing What cells are a replication of the earlier study ? So, which set of SEs will allow us to check if we got the replication, and then go on to see of we get the same results with the new topic ? Yep, SE of Type of Instruction, for each Topic...

#1 I have previously demonstrated that rats learn Y-mazes faster than do hamsters. I wonder if the same is true for radial mazes? (DV = time to complete maze) Your Turn – “Draw the boxes” & use or = to depict the interaction. Species Rat Hamster Maze Y Radial < Major Psych Soc Topic Statistics Ethics ??? = SE of Species for each Type of Maze #2 I’ve discovered that Psyc and Soc majors learn statistics about equally well. My next research project will also compare these types of students on how well they learn research ethics. (DV = % correct on exam) SE of Major for each Topic

Sometimes the RH: about the interaction and one of the main effects are “combined” this is particularly likely when the expected interaction pattern is of the > vs. > type Here’s an example… Group therapy tends to work better than individual therapy, although this effect is larger for patients with social anxiety than with agoraphobia. Type of Therapy Group Indiv. Anxiety Social Agora. > > Main effect RH: > Int. RH: So, we would examine the interaction by looking at the SEs of Type of Therapy for each type of Anxiety.

Young girls have better verbal skills than motor skills, however the difference gets smaller with age (DV = skill score) Type of Skill Verbal Motor Age 4 yrs 9 yrs > > Confession is considered more convincing than eyewitness testimony. This preference is stronger for jurors than for judges. DV = convincingness rating) Type of Evidence Confession Witness Rater Judge Jurors > > Your Turn – “Draw the boxes” & use or = to depict the interaction. Tell which set of SEs you will use! SE of Skill for each gender SE of Type of Evidence for each Rater