Message/Author 

Daniel posted on Monday, February 14, 2005  6:10 pm



Hi, Is use of bootstrap standard errors for calculating indirect effects better than WLSMVderived stanadard errors when working with categorical outcomes? When I calculate indirect effects without bootstrap, I get significant indirect effects. However, when I bootstrap, I get nonsignificant effects. 


It is sometimes the case that bootstrap standard errors are larger than model estimated standard errors. This would result in some effects becoming nonsignficant. 

Daniel posted on Tuesday, February 15, 2005  10:04 am



Which method is generally more trustworthy with orderedcategorical data? Is there a ruleofthumb? 


I don't know. I think it would depend on many factors. 

Daniel posted on Friday, February 18, 2005  3:53 pm



Linda, one of my indirect effects (a*b) in this mediation analysis is not significant. However, each individual path (path a and path b) from the exogenous variable to the slope factor is significant. Do you have any idea how I would report this finding? Essentially, the pieces are significant but not the whole indirect effect. 

BMuthen posted on Friday, February 18, 2005  5:04 pm



This can happen. For example, if the a and b parameter estimates are positively correlated, this increases the standard error yielding nonsignificance. 

J. Williams posted on Tuesday, February 22, 2005  11:30 am



What is the sample size in the analysis where the z was sig. and the percentile was not? We found this to occur rarely in simulation data with continuous variables. In most cases the significant z is a Type I error though. When sample size is 200+, the z is never signifcant if the percentile is not. 

bmuthen posted on Saturday, February 26, 2005  11:55 pm



Let's see if Daniel replies. 

Marion posted on Monday, July 04, 2011  1:17 pm



Hello, I'm analysing a mediation model and want to test the indirect path with bootstrapping. Mplus is doing it, but never completely. e.g.: Number of bootstrap draws Requested 5000 Completed 2950 Can you help me? Why is Mplus doing that? Does it tell something about my model? Thanks. 


That typically says that your model is difficult to estimate for your data, so that for different subsets of the data the estimation does not converge properly. For instance, the sample size may be small or the model illfitting. You can send your files to support if you want guidance on that. 

Marion posted on Tuesday, July 05, 2011  5:55 am



Dear Mr. Muthen, I would love to get some guidance on that, because I've already tried lots of things. What do I have to send to you? Whats the email address? Thank you so much. 


If you have a valid Mplus support contract, you should send it to support@statmodel.com. 

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