In a quantitative study, three variables-- I am comparing two variables (self-concept & well being) with another variable (intent to leave profession). I am predicting to see a positive correlation.
I am using ANOVA in SPSS but I am not sure this is the best choice?
Thank you
That depend of your aim in recherche,if you want to measure the impact some of variables on a variable you can using regression analysis , but if you want to measure the relation you can using correlation
ANOVA is a special case of regression anlysis , but if the independent/predictor variable is categorical, you must use ANOVA, otherwise use regression analysis.
On the other hand, when the dependent variable is dichotomous or categorical, you must use Logistic GLM.
It depend mostly on your DV. If the 2 variables are expected to be dependent on the Third I recommend multivariate regression. If you expect the third to be the DV then ordinary multiple regression should be easiest. I am assuming all variables are continuous. If not, more specialized methods may be needed. This link may be helpful but many people confuse multivariate with multiple regression. You would want multivariate if you have 2 DVs and multiple if one DV.
HTH, David Booth https://www.google.com/search?sxsrf=ALeKk03rTfJwhXv8u_i_fCbZmQl71u6wtA%3A1588734959282&ei=7yuyXtThEIW-tAbLtIvIBA&q=multivariate+linear+regression+spss&oq=multivariate+linear+regression+spss&gs_lcp=CgZwc3ktYWIQAzICCAAyBAgAEB4yBggAEAgQHjIGCAAQCBAeMgYIABAIEB4yBggAEAgQHjoECAAQRzoHCCMQsAIQJzoGCAAQBxAeOgQIABANOggIABAIEAcQHjoGCAAQDRAeUNzEA1jR4QNgyvkDaABwAngAgAFoiAH1BJIBAzUuMpgBAKABAaoBB2d3cy13aXo&sclient=psy-ab&ved=0ahUKEwiUlY_3op7pAhUFH80KHUvaAkkQ4dUDCAw&uact=5
You can make a predictive model of linear regression, although I would recommend a model of structural equations (SEM) that evaluates the effect of both variables in the abandonment of the profession, through this model you can argue the proposed theoretical explanatory model.
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