Subgroups bootstrap error

Questions about the implementation and application of the PLS-SEM method, that are not related to the usage of the SmartPLS software.
Post Reply
Filippo
PLS Junior User
Posts: 1
Joined: Wed Aug 08, 2018 11:23 am
Real name and title: Filippo Marino

Subgroups bootstrap error

Post by Filippo »

Hello everyone,

I'm using SmartPLS 3 for my master's project. Since I collected data in a geographically broad area I ran the PLS and the bootstrap algorithms for the complete dataset (n tot=249) and also for 2 subgroup (n1=179 and n=76); I also checked for heterogeneity by conducting Multigroup Analysis. Until I had in my PLS model 7 variables pointing at the final endogenous variable everthing worked.

However, once I included 1 and/or 2 more variable(s) to my model (one mediator and one moderator), the boostrap report for the smaller subgroup (n=76) gave me NA values for standard deviation and blank values for T and p values.

Do you think the reason is the sample size of this subgroup? According to Hair, Jr et al. (2014) who cited Cohen (1992), n=76 should work for PLS at 1% significance, mininum R^2= 0.5 and 9 arrows pointing at a construct. Does this work also for the bootstrap analsysis?

Thank you!
jmbecker
SmartPLS Developer
Posts: 1284
Joined: Tue Mar 28, 2006 11:09 am
Real name and title: Dr. Jan-Michael Becker

Re: Subgroups bootstrap error

Post by jmbecker »

There can be potentially many reasons. I would guess that the new variables do not have sufficient variance for one of the subgroups. That can especially happen with moderators that are very similar to your grouping variable. Within the groups you may have a variance of zero for those variables (only the same values) or a very limited variance that leads to zero variance in only some of the randomly drawn bootstrap samples. Variables with zero variance cannot be used in a PLS model.
Your variables might also be highly collinear in the subgroups which could lead to problems in some of the bootstrap samples.

Both problems are indirectly related to sample size as they are more likely to occur if you have only a few observations.
Dr. Jan-Michael Becker, BI Norwegian Business School, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de
Post Reply