Re: Interactions binary logistic regression

Posted by PhD student on Jan 23, 2017; 9:47am
URL: http://spssx-discussion.165.s1.nabble.com/Interactions-binary-logistic-regression-tp5733602p5733733.html

After the reading of this very helpful book (Heck, Thomas & Tabata, 2010), it would appear that GEE are particularly appropriate for my data. However I still have a little question in how to explain my significant 3 way interaction.

Just as a reminder, my participants (Anxiety Disorders vs. Control) carried out 8 trials resulting from the combination of a 2 (Formulation : Gain vs Loss) and a 4 (Level of risk : 20% vs 40% vs 60% vs 80%) within subject factors. In each trial, they had to choose between a safe and a risky option.

As I know that it is easy to make mistakes with these “recent” analyses (I did not find any well-written example in my field and any of my supervisors/colleagues know much about this analysis), I will briefly explain how I proceed.

First, I chose a logit link and a binomial error distribution. Then, in order to select the most appropriate working correlation structure, I ran 3 different models using either the independent, autoregressive or exchangeable correlation structure. I found that QIC for the independent, autoregressive and exchangeable were in the same range (i.e., vary less than 2 points between these 3 structures). As complete independence between trials within the same individual is not credible and as any of my participants report changing his strategy across trials, I selected an exchangeable working correlation structure.

Second, I ran a full factorial model (including 3 main effects: Group, Formulation and Level of Risk; three 2-way interaction: Group X Formulation, Group X Level of Risk and Formulation X Level of Risk; one 3 way interaction: Group X Formulation X Level of Risk). The 3-way interaction was significant, thus I did not interpret main effects or 2-way interaction and I focused only on the significant 3-way interaction. In order to explain this significant 3-way interaction, I ran pairwise comparison corrected with the bonferonni procedure and I described comparisons that answered my hypotheses.
What do you think about this analysis ?


Here is my syntax :
* Generalized Estimating Equations.
GENLIN choice (REFERENCE=LAST) BY Group Formulation Risk (ORDER=ASCENDING)

/MODEL GROUP FORMULATION RISK GROUP*FORMULATION GROUP*RISK FORMULATION*RISK        GROUP*FORMULATION*RISK INTERCEPT=YES
DISTRIBUTION=BINOMIAL LINK=LOGIT
  /CRITERIA METHOD=FISHER(1) SCALE=1 MAXITERATIONS=100 MAXSTEPHALVING=5 PCONVERGE=1E-006(ABSOLUTE)
SINGULAR=1E-012 ANALYSISTYPE=3(WALD) CILEVEL=95 LIKELIHOOD=FULL
  /EMMEANS TABLES=GROUP*FORMULATION*RISK SCALE=ORIGINAL COMPARE=GROUP*FORMULATION*RISK CONTRAST=PAIRWISE PADJUST=BONFERRONI
  /REPEATED SUBJECT=ID WITHINSUBJECT=Trial SORT=YES CORRTYPE=EXCHANGEABLE ADJUSTCORR=YES COVB=MODEL MAXITERATIONS=100 PCONVERGE=1e-006(ABSOLUTE) UPDATECORR=1
  /MISSING CLASSMISSING=EXCLUDE


Thank you again for your amazing support!