**Re: ANOVA and mediation- could someone CHECK over this with me? Help gratefully recei**
Then there's the mediation analysis. So I have quickly drafted this out and have pasted below. I used the preacher and hayes SPSS macro to do the analysis on pre-cleaned data. I am not sure how to report, what to report etc so I would appreciate any comments on what is below plus any ideas for papers I could look at for well reported (pref psychology type) mediation analyses - I've found a couple but as I'm not sure what I'm looking at it's hard to judge what is "well reported"! As always, your advice and input is very gratefully received. I should say that here we are looking to test whether the impact of HIV group (HIV or control) has an impact on the quality of life over and above the impact of socio-economic status (SES) - so we are hypothesis driven not just fishing!

Mediation analysis was completed to explore the degree to which SES (wealth basically) is affecting the relationship between case and quality of life. There are three relevant quality of life variables - which I explain in the text I've drafted in full and dull detail. So I've got a model of IV = HIV group or control group, mediator = SES which is a wealth index and then the DVs are one at a time of the three quality of life variables. (There is a conceptual reason why I want to keep these three variables separate at this time, although there is a potentially more complex story as in reality the three variables do correlate to a small degree with one another).

In all cases, the effect of HIV group (independent variable) on the mediator SES was 1.0869. Table *** provides the summary analysis (I've copied and pasted this below - it looks a bit scrappy though).

In all cases, the relationship between HIV group (case or control) and the WHOQOL domain remained significant when the effect of SES was accounted for. As such, there is no evidence of full mediation of HIV group and QOL by SES.

Although using the Preacher & Hayes (2004) method suggests that partial mediation by SES was significant at p<0.05 in all cases (as zero is no within the 95% confidence interval or CI), the actual effect of SES on the HIV group to QOL relationship is very small. There is no agreed upon way of calculating how much of the variables effect is due to mediation (Hayes, Preacher, & Myers, 2011).

One method is to calculate the proportion of the total effect that is mediated (to create a percentage by dividing indirect effect by total effect and multiplying by 100), as shown in table ***. This illustrates the minimal proportion of the relationship between HIV group and QOL that was found to be mediated by SES.

Table *** Summary of Mediator analysis of socio-economic status and the relationship between HIV case and WHOQOL 1, 2 and 4.

DV Effect on SES on DV Direct effect of HIV group on DV Indirect effect 95% CI of indirect effect Total effect Proportion %

QOL 1 0.0491 1.0404** 0.0100 0.0076 – 0.0007 1.094** 0.91

QOL 2 0.0537* 1.6267** 0.0137 0.0084 – 0.0024 1.685** 0.81

QOL 4 0.0937** 1.6338** 0.0213 0.0103 – 0.0051 1.736** 1.23

* significant at p<0.05 **significant at p<0.01