Next Upcoming Google+ Hangout: Tuesday, August 27 @ 7PM (CST) - To Participate CLICK HERE
Search For Topics/Content
Top
Discussion Forum Topics
Find a Blog Entry
- Confusing Stats Terms Explained: Internal Consistency
- R Is Not So Hard! A Tutorial, Part 4 (repost)
- Confusing Stats Terms Explained: Heteroscedasticity (Heteroskedasticity)
- How to Create APA Style Graphs and Then Teach SPSS to Do it Automatically!
- Wonderful "How-To" Resources for Learning Structural Equation Modeling (SEM) with AMOS
- Interpreting the Intercept in a Regression Model (repost)
- Why You Shouldn't Conclude "No Effect" from Statistically Insignificant Slopes (repost)
- To syndicate or not to syndicate, that is the question...
- Please Vote on the "Top Confusing Stats Terms"
- How to Conduct a Repeated Measures MANCOVA in SPSS
- The Worst Mistake Made on a Dissertation Is...
- Moderating Effects with Seemingly Uncorrelated Variables
- Using Syntax to Assign 'Variable Labels' and 'Value Labels' in SPSS
- How to make SPSS produce all tables in APA format automatically!
- Confusing Stats Terms Explained: Residual
- Confusing Stats Terms Explained: Multicollinearity
- Confusing Stats Terms Explained: Standard Deviation
- Top Ten Tips for Data Analysis to Make Your Research Life Easier!
- Within-Subject and Between-Subject Effects: Wanting Ice Cream Today, Tomorrow, and The Next Day…
- Bonferroni Correction In Regression: Fun To Say, Important To Do...
- Put aside your fears and be wrong already!
- Trade Your Stats "Truths" for Stats Arguments...
- Data Transformations: statistical voodoo or truth serum for your data?
Hi Jermey,
I wonder can you help me out, I think this is a reasonably easy question but I am a novice in the area of multiple mediation and I haven't been able to figure this problem out and I'm sure you'd answer this pretty quickly.
I have three hypothesised mediators M1 (Team member exchange), M2 (Leader member exchange), and M3 (Perceived organisational support) which I argue will mediate the relationship between two independent variables [attachment styles (avoidance and anxiety)] and information exchange with colleagues at work (N=192). I ran simple mediation models for each of these mediators (without controlling for the effects of the other mediators) and found that M1 (TMX) fully mediated the effect of attachment avoidance and anxiety on information exchange. M2 (LMX) fully mediated the effect of attachment avoidance on information exchange and partially mediated the effect of attachment anxiety on information exchange. For M3 - no mediation was found.
When I enter the three mediators into Preacher and Hayes' (2008) INDIRECT, I found that both M1 (TMX) and M2 (LMX) mediated the link between avoidance and information exchange whilst as expected no mediation was found for M3 (POS). For attachment anxiety no mediation effect was found for any of the mediators. I am okay with making theoretical conclusions on this findings. However, given that I found full mediation for M1 (TMX) and partial mediation for M2 (LMX) in the effect of attachment anxiety on information exchange when I ran simple mediation models should I report this information also? Or just report the multiple mediation findings using INDIRECT. I would like to show the mediation effect of M1 (TMX) and M2 (LMX) for anxiety however is this poor practice... I'm not sure, any advice would be great- I have a conference next week and need to discuss these findings and I'm not sure myself what to make of it.
Also when I tested the simple mediation for M3 I initially decided to include only M1 and M2 in INDIRECT, however this caused the bootstrap result for M2 to reduce to insignificance. Should I include all three hypothesised mediators on INDIRECT or just the two that had significant mediation in the simple mediation tests?
Best Wishes and Thanks for the blog!
Rachel.