I surveyed 400 participants and each participant received 8 images to analyze, each image with the manipulation of 3 factors (A, B, C, AB, AC, BC, ABC, Control - no changes). Then, they answered the same question for each image, choosing one option of 4 (W, X, Y, Z).
I am analyzing the data in SPSS. I used the Repeated Measures Mancova, including my IVs (A, B, C) as dummy variables (0 - not applied, 1 - applied). Then, I included my DVs (A_W, B_W, C_W, AB_W, AC_W, BC_W, ABC_W, Control_W...repeating for X, Y, and Z) also as dummy variables (0 - option not chosen and 1 - option chosen). My covariates are age, gender, and duration.
I would like to know if this is a good model to analyze this data.
Hello Erica Castilho Grão. You wrote:
Then, they answered the same question for each image, choosing one option of 4 (W, X, Y, Z).
Please spell out what exactly the 4 options (W to Z) are. It seems they must be 4 levels of some categorical variable. But are the categories ordered? Or is it a purely nominal variable? Thanks for clarifying.
Without more information about the specific research question, variables, and design, it is difficult to evaluate whether a model is appropriate for Repeated Measures of MANCOVA. However, here are some general guidelines to consider when building a Repeated Measures MANCOVA model:
In summary, building an appropriate Repeated Measures MANCOVA model involves careful consideration of the research question, selection of appropriate variables and factors, selection of an appropriate statistical model, and checking the assumptions of the model. It is important to consult with a statistician or other expert in data analysis to ensure that the model is appropriate for the research question and data.
Sample size matters. You have many variables and interactions. Your covariates should be correlated with the dependent variables. Check multivariate normality. Building a model can be proposed but not defined before hand.
- Badges
- Science topic
- Similar topics
- Correction