I have a quick question regarding indirect effects. I have a model with interval scaled IV and M, but the DV is nominal scaled (binary). Besides odds ratios Mplus provides standardized and unstandardized coefficients for the b path (using MLR). Using model indirect displays an indirect effect based on a*b, however, I am not sure if Mplus already transforms standardized and unstandardized coefficients for b so that model indirect comes to a valid result. If this is not the case, how do I transform coefficients for b appropriately?
Not sure what you are asking so let me state a few facts to see if they help.
Mplus gives the a*b indirect effect in unstand. and stand. form. The stand. value is the same as the product of a stand. and b stand. With a binary outcome you should use the counterfactually-based effects.
I would like to calculate a path model with 1 continuous IV, 3 continuous mediators (in parallel), 1 sequential continuous mediator and 3 DVs (2 are continuous, 1 is binary). I am using ML estimation (I am thus calculating a logistic regression) and defined the binary outcome as categorical. Using MODEL CONSTRAINT, I calculated all possible indirect effects (BOOTSTRAP = 10000; CINT(bcbootstrap)). To obtain the the correct estimates of the indirect effect involving the binary DV I exponentiated the indirect effects (e.g., ORa1b1 = exp(a1*b1); ORa1b1d1=exp (a1*b1*d1). Is this approach correct? What about direct effect involving the binary DV - is the estimation a B coefficient in the output based on logistic regression? When looking at the output, I also get the odds ratio in case of the direct effect but I don't not the CIs (however, I do get those for these indirect effects). How do I get the CIs of the odds rations for the direct effects? What would be the best way to run the same analyses if the DVs would be ordinal with 4 categories (e.g., which estimator, bcbootstrap or other approaches to calculate the significance of indirect effects)? Many thanks for your help.
With ORs, you should use non-symmetric confidence intervals to decide on significance - use confidence intervals from bootstrapping. The printed p-values assume that symmetric confidence intervals are relevant.
When I add bootstrapping, the 95% CI for A1B1 (-0.593, 0.752) crosses 0, but not for the OR (0.553, 2.121). These are not labeled in the output as non-symmetric - is there a different command to request those?
Also, I'm not sure what the difference is between A1B1 and ORA1B1? If the indirect effect is not significant, why would I interpret the OR?