Posted by
Maguin, Eugene on
Jul 14, 2016; 1:33pm
URL: http://spssx-discussion.165.s1.nabble.com/Non-Equivalent-Control-Groups-Design-Quasi-Experimental-Design-tp5732723p5732728.html
As I understand your procedure, you have two between factors: model weight category and BMI category. From your reply to David, the dependent variables seem to be "continuous". Computationally, this fits an ANOVA, GLM in spss. I'd say you should be interested in the interaction. You'll get F values and associated p values. Depending on the audience for your work, I think the problem you'll have will be defending your results against alternative explanations such as those David pointed out.
Gene Maguin
-----Original Message-----
From: SPSSX(r) Discussion [mailto:
[hidden email]] On Behalf Of kat92
Sent: Thursday, July 14, 2016 5:17 AM
To:
[hidden email]
Subject: Re: Non-Equivalent Control Groups Design/ Quasi-Experimental Design
Hi David,
Sorry I didn't ask clearly in the previous message. By "body image", I was referring to "body satisfaction". I used Stunkard's Figure Rating Scale before and after the picture-viewing, by asking the participants to choose their current body shape and ideal body shape among the 9 body shapes provided. Therefore, the body image changes is measured by calculating the difference of ideal and current body shape (for pre- and post-test), the greater the difference indicates the greater body dissatisfaction one has.
And my hypothesis was that participants (especially those who were
overweight) will have lowered body dissatisfaction after viewing pictures of models with similar body shape with them.
"Weight loss desire" is measured as one's ideal weight subtracted by one's current weight. I hypothesized that the participants will have lowered weight loss desire (i.e. smaller difference between ideal weight and current weight in post-test compared to pre-test) after viewing over-weight or normal weight model pictures.
As I did not randomly assign the participants to the groups for picture-viewing (I made sure each picture-viewing condition had equal no. of participants in each BMI classification), I think it should not be considered as random assignment? One of my concerns was that participants in each condition had different level of weight loss desire and body satisfaction due to their own weight. By having 3 conditions (9 participants in each BMI classification x 3 classifications = 27 participants each condition), the difference within and between group might be unpredictable, so I wonder if there's a way to control any (DVs affected by weight).
Thanks!
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