2-Way Anova JASP final update (1) PDF

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Psych 248 - Two-Way ANOVA Name THALIA ORLANDO The goal of the two-factor ANOVA is to evaluate the mean differences that may be produced by two factors acting independently or by two factors acting together. The mean differences among the levels of one factor are referred to as the main effect of that factor. Interaction occurs whenever the mean differences between individual treatment conditions are different from what would be predicted from the overall main effects of the factors separately. PART 1: Using JASP to analyze two-way ANOVA problems. Open the data file called Dating.csv in JASP In JASP, select ANOVA > Classical > ANOVA . How long will someone be able to speak to a person they approach? Looking at the approach type and attractiveness level of the person approaching; we want to see if there is an effect on the length of time that they interact with the recipient. Label the appropriate levels in the IVs for attract and approach. Attract: 1-attractive; 2-unattractive Approach: 1-conversation; 2-humor; 3-pick-up-line Transfer Time to Dependent Variable. Put attract and approach as Fixed Factors. Under Options choose Descriptive Statistics. Under Descriptive Plots choose attract for Horizontal Axis and approach for Separate Lines. (Note that when you label the variables, long names will distort the graphs so use shortened terms, such as Psycho, CB, and ERP for therapies or Zinc for meds.) Under Assumptions Check, check Homogeneity Tests. ****Levene’s Test will be significant meaning homogeneity has been violated. Ignore this for this lab and continue like normal as if it was not significant. Run the post-hoc test on the factor(s) or interaction term that is significant. Paste the ANOVA table and the Descriptives Plot here. What is a factor? A factor is the independent variable. What is a level? A level is the different group within the independent variable What is the F for Factor A - Attract? 10.143 and for Factor B - Approach? 107.664* and for the interaction Affect? 8.472 Put a * by those that are significant. Looking at the plot, which approach had the greatest effect?HUMOR Was there an interaction between attractiveness and approach? How can you tell? YES BECAUSE THE LINES ARE NOT PARALLEL Based on the Descriptives, the F-tests and the plot, write a few sentences in APA style to describe these results. Include which effects are significant and then describe the findings in terms of this study (including both IV and DV). Remember that if significant, interactions should be discussed first and are the primary findings, because the main effects are qualified by the interaction. There is a significant interaction between the time and the level of approach. F(2)= 107.664, p< .001, n^2=5. Part II We want to run a study to see if different behavioral therapies (1:Psychodynamic; 2:Cognitive Behavioral; 3:Exposure and Response Prevention) and different medications (0:Placebo; 1:SSRI; 2:Zinc Supplement) work differently in promoting weight change among patients with anorexia. By running a two-way ANOVA, we can see how the different therapies and medications affect weight change both separately and together (i.e. their interaction).

With JASP open the file called Anorexia.cvs Write out the three alternative hypotheses in words.

1. The medication will cause an increase in the weight change. 2. The medication and therapy will both cause a significant increase in the weight change. 3. The therapy will result in an increase in the weight change. 4. Look at the Medication variable. How many levels does it have? 2 5. Look at the Therapy variable. How many levels does it have? 3 6. How many different groups would there be in this ANOVA analysis? 2 In JASP, select ANOVA > Classical > ANOVA . Label the appropriate levels in the IVs for therapy type and medication. Behavioral therapies: 1-Psychodynamic; 2-Cognitive Behavioral; 3-Exposure and Response Prevention Medications: 0-Placebo; 1-SSRI; 2-Zinc Supplement (Note that when you label the variables, long names will distort the graphs so use shortened terms, such as Psycho, CB, and ERP for therapies or Zinc for meds.) Transfer WeightChange to the Dependent Variable box and both the Therapy_Type and Medication variables to the Fixed Factors box. Under Options choose Descriptive Statistics. Under Assumptions Check, check Homogeneity Tests. Under Assumptions Check, select Homogeneity tests. 7. Was the Levene’s Test of Equal Variances significant? Can we assume homogeneity? No for significance, yes for assuming homogeneity of variance. 8. Under Descriptives Plots: Put Therapy_Type under Horizontal Axis and Medication Under Separate Lines. Click Display Error Bars and choose Standard Error. Paste the plot below.

9. Report the results of the ANOVA in the table below. Sources of Variance

Sum of Squares Degrees of Freedom Mean Square F-value P-value

Therapy

8.810

2

4.405

1.001

0.37

Medication

295.392

2

147.696

33.575...