Presentation on theme: "DFA & MANOVA PS503 - Unit 7. The Unit 8 Project We will be doing a Factor Analysis on the “complete_mooney_bp.sav” dataset from the Unit 5 assignment."— Presentation transcript:
The Unit 8 Project We will be doing a Factor Analysis on the “complete_mooney_bp.sav” dataset from the Unit 5 assignment
The Unit 8 Project We will be looking at four variables: Assertiveness as measured by the “rath” variable a higher number meaning MORE assertive
The Unit 8 Project We will be looking at four variables: Assertiveness “rath” Social desirability as measured by the “Crowne-Marlowe” variable A higher score means the person has a greater desire to behave in socially desirable ways
The Unit 8 Project We will be looking at four variables: Assertiveness “rath” Social desirability “Crowne-Marlowe” Tendency to outwardly express anger As measured by the “axout” variable A higher value means that the person is more likely to express anger outwardly
The Unit 8 Project We will be looking at four variables: Assertiveness “rath” Social desirability “Crowne-Marlowe” Tends to outwardly express anger “axout” Tendency to hold anger in As measured by “axin” variable A higher value means MORE likely to withhold anger
The Unit 8 Project We will be looking at four variables: Assertiveness “rath” Social desirability “Crowne-Marlowe” Tends to outwardly express anger “axout” Tends to hold anger in “axin” Hopefully these look familiar, they were used in the Unit 5 project
The Unit 8 Project We are interested in determining if there are any underlying (latent) variables that might be influencing these measured variables. We may not be able to identify these “Factors” but we can use the Factor Analysis to see how much influence they have
The Unit 8 Project Run the analysis as outlined in the instructions. If you find any buttons or check boxes already filled in, leave them filled in.
The Unit 8 Project You get a number of output tables. The first is simple descriptive stats The means are not comparable to each other, each variable has its own scale
The Unit 8 Project There is a correlation matrix How does each of our variables correlate to the others?
The Unit 8 Project Three correlations are significant Crowne-Marlowe : Axin Rath : Axin Rath : Axout
The Unit 8 Project Be able to describe the relationships What direction do they go in? What does this mean in terms that your mom can understand?
The Unit 8 Project Pay attention to Rath, it is correlated to both of the anger variables
The Unit 8 Project Notice that Crowne-Marlow is only significantly correlated to one of the anger variables Although the other is pretty close to significance But the significant one differs in the direction of the correlation from what one might expect
The Unit 8 Project This table is an important one, it is where we determine how many latent factors there are. We do this by setting a lower limit on the Eigenvalue An Eigenvalue is basically the proportion of variance explained by the variable divided by the proportion of variance unaccounted for: SS between / SS within
The Unit 8 Project For a latent factor to have a significant influence, we want the Eigenvalue to be greater than one (1). This would mean that there is more variance accounted for by the factor (between) than that which is unaccounted for (within) : SS between > SS within You can see that only two of these latent factors meet this req’t.
The Unit 8 Project There are four factors listed, you should discuss ALL four in your project, indicating which ones appear to be significant enough to consider as “real” latent factors The rubric asks you to discuss the % of variance for each factor It also asks you to discuss the cumulative % of variance (which I think is kind of silly)
The Unit 8 Project The big problem with Factor Analysis is that, while we can use it to determine if there are underlying factors at work, we may not get a clear picture of what those factors are But we can hypothesize about what they are, and perhaps design later research to investigate them more directly
The Unit 8 Project As usual: APA style, 12-point font, Times New Roman Describe things in detail if you can Show your reasoning, if it’s sound, I’ll give credit Images are okay but do NOT replace discussion Reference the text when describing various elements (such as % of variance, Eigenvalue, etc) Don’t worry about the page length, I’m interested in comprehension and presentation Use the rubric, make sure everything on it is in your paper
Unit 7: DFA & MANOVA In Discrete Function Analysis (DFA) we are basically using (several) continuous variables to predict group membership(s) In Multiple Analysis of Variance (MANOVA) we are using group membership(s) to predict outcomes on continuous variables They are essentially two sides of a coin
Unit 7: DFA & MANOVA Example: Let us say we are interested in the efficacy of several approaches to sex education: No sex ed Abstinence-only programs Full-blown health programs And let’s include a second variable for good measure: Gender Male Female
Unit 7: DFA & MANOVA They can be used in tandem, to some extent. Example: And we have some outcome variables Adolescent sexual activity measure(s) Unintended pregnancy rate Rate of contraction of STIs
Unit 7: DFA & MANOVA They can be used in tandem, to some extent. Depending upon the time involved and the purpose for which we are doing our research, either of these analysis methods could be used First… MANOVA
Unit 7: DFA & MANOVA We can find and categorize a number of randomly selected sex ed programs We can then collect data on the sexual activity, occurrence of unintended pregnancies (perhaps the proportion of the class that gets pregnant within five years of the sex-ed program), and contraction of STIs And we can analyze these data to determine if different sex-ed programs (and/or different genders) can be used to predict outcomes
Unit 7: DFA & MANOVA Alternatively, we could use DFA to look backwards Take the data compiled by a number of different public health organizations that look at teenage sexual activity, pregnancies, and contraction of STIs. Often such data includes information on locale permitting determination of the typical sex-ed programs available to the people tracked We could use this data to attempt to predict which type of sex education program led to different results on these outcome variables
Unit 7: DFA & MANOVA Both of these analysis methods are very useful, as you can see Used individually they can tell us a great deal about behavior, group membership, outcomes, etc. Used together they can reinforce each other, lending support to particular hypotheses. Questions?