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I have more than one question, if you can help:

  1. I have a regression model with 5 control variables each with 5 categories. I am wondering if there's any way, that can be also considered methodologicaly correct, to use them in a multiple regression analysis without transforming them into dummy coded variables? Problem is I forgotten to do this, already completed most of the analysis and now would have to take it from the beginning. After dummy coding and repeating the tests, there are differences in R change, they explain some extra 5% more and there is a small decrease in the proportion explained by the predictors.

  2. Say I'm conducting a mediation analysis. From what I understand, reverse causality would mean my outcome predicts my mediator. How about the case when my mediator predicts my predictor, how would that be called? Theoretically, it is possible, I've tested both scenarios and they are significant. Should I report them both, would it be correct? (mediation tested in spss BK steps and Hayes macros).

  3. I've used Hayes' macros to test the mediation. Problem is that using same set of variables but different macros gave me slighlty different results. I've read that it can be because of the sample size, because cases with missing values are deleted and won't be used in the analysis. But this doesn't seem the case. Why would the results be different if the macros are supposed to test the same mediation?

Any thoughts greatly welcomed.

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Regarding 1. No, I don't think so. But any statistical program (R, SAS, SPSS) will do this for you. Unless you had numbers for the different categories, in which case what you did is just wrong. What software did you use? Can you show us code? (From question 2 it looks like you use SPSS).

Regarding 2. Can you please give us context? What variables are these? If M is "causing" X, then it sounds like X is mediating the relationship between X and Y.

Regarding 3. I Googled Hayes macro and found that he has written different macros for different kinds of mediation. Given that, it isn't surprising that they give different answers. What are you trying to do?

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  1. I have categories for age, gender, education, organization size, type, department, position in a firm. Yes, I had numbers first time I did the analysis, now I've recoded them according to a reference category. So this means first time the approach was wrong ... I'm working with SPSS.
  2. Say my variables are socialization in a firm and fit between a person and a firm. Theoretically it is possible for socialization to influence fit which in turn can influence turnover and the other way around, for fit to influence socialization which in turn can influence turnover. Then can I use both hypothesis about the mediation?
  3. I've used two macros which both allow to test multiple mediation. Even so, I'm thinking all macros can test simple mediation, for example, only with the predictor, mediator and outcome included. Shouldn't the results be the same in this case?
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