Hi,
To make a multigroup analyses by gender, I divided my research sample to two data sets using SPSS (Female and male), than I used SmartPLS 3 to test my model depending on the two data sets, after runing SmartPLS, I got two models with defferent results.
Is this way correct to make multigroup analyses by gendre or age?
What is the statistics should I get from SmartPLS to justify the defference between the two models?
SmartPLS Team, thank you
Multigroup analyses
- cringle
- SmartPLS Developer
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- Real name and title: Prof. Dr. Christian M. Ringle
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Re: Multigroup analyses
First, you do not need to use SPSS to split your data set. SmartPLS has in-built options to create groups of data. Double click on your data set and use the group generation functions in the menu.
Second, when runnding the multigroup analyis, you get the results of several tests that show you if the difference is signifficant. E.g., when using PLS-MGA: All probabilities above 0.95 and blow 0.05 indicate that the group differences are significant.
Regards
Second, when runnding the multigroup analyis, you get the results of several tests that show you if the difference is signifficant. E.g., when using PLS-MGA: All probabilities above 0.95 and blow 0.05 indicate that the group differences are significant.
Regards
Prof. Dr. Christian M. Ringle, Hamburg University of Technology (TUHH), SmartPLS
- Literature on PLS-SEM: https://www.smartpls.com/documentation
- Google Scholar: https://scholar.google.de/citations?use ... AAAJ&hl=de
- Literature on PLS-SEM: https://www.smartpls.com/documentation
- Google Scholar: https://scholar.google.de/citations?use ... AAAJ&hl=de
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Re: Multigroup analyses
Thank you Pr. Christian M. Ringle
You are so helpful
Thank you
You are so helpful
Thank you
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- PLS Junior User
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- Real name and title: Christian Koch
Re: Multigroup analyses
Hallo Herr Prof. Ringle,
muss der Wert definitiv unter 0,05 und über 0,95 oder kann er auch gleich 0,05 oder 0,95 sein?
Kann das Signifikanzlevel eigentlich im Bootstrapping-Dialog für die MGA geändert werden? Wenn ich es auf 0,02 ändere, sind dann bspw. aller Werte unter 0,02 und alle Werte über 0,98 signifikant?
Viele Grüße
Christian Koch
muss der Wert definitiv unter 0,05 und über 0,95 oder kann er auch gleich 0,05 oder 0,95 sein?
Kann das Signifikanzlevel eigentlich im Bootstrapping-Dialog für die MGA geändert werden? Wenn ich es auf 0,02 ändere, sind dann bspw. aller Werte unter 0,02 und alle Werte über 0,98 signifikant?
Viele Grüße
Christian Koch
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Re: Multigroup analyses
Dear Mr. Koch:
The level of significance should be set on the basis of your target journal. 5% is more conservative but there are also journals that accept higher levels up to 10%. The setting in SmartPLS is primarily for calculating the confidence intervalls. You can see the change in the output report in the head of confidence intervalls tables.
Best regards
MJ
The level of significance should be set on the basis of your target journal. 5% is more conservative but there are also journals that accept higher levels up to 10%. The setting in SmartPLS is primarily for calculating the confidence intervalls. You can see the change in the output report in the head of confidence intervalls tables.
Best regards
MJ
Re: Multigroup analyses
Hello community! : )
after checking my research model with the datasets of all participants (81) of my survey, now I want to further evaluate whether there are differences between male and female participants.
Here, first I created the new groups "female"(22) and "male" (59). Then I started the PLS Algorithm, applied the user groups and was able to switch between ALL/female/male. As I need the T-values, I also started the Bootstrap calculation and also here I applied the user groups but now, I just can switch between ALL/male.
Do somebody know why female is missing and how do I get the results for that?
I also tried to start the Multi-Group Analysis but I get the error message "An error occured during the outside estimation for latent variable "BIU". (Double click for more information!)". Here the double click says remove the variable or increase sample size - both is no opportunity.
Any suggestions how to solve the problem?
thanks and best,
Patrick
after checking my research model with the datasets of all participants (81) of my survey, now I want to further evaluate whether there are differences between male and female participants.
Here, first I created the new groups "female"(22) and "male" (59). Then I started the PLS Algorithm, applied the user groups and was able to switch between ALL/female/male. As I need the T-values, I also started the Bootstrap calculation and also here I applied the user groups but now, I just can switch between ALL/male.
Do somebody know why female is missing and how do I get the results for that?
I also tried to start the Multi-Group Analysis but I get the error message "An error occured during the outside estimation for latent variable "BIU". (Double click for more information!)". Here the double click says remove the variable or increase sample size - both is no opportunity.
Any suggestions how to solve the problem?
thanks and best,
Patrick
Re: Multigroup analyses
I also tried the Multi-Group analysis and get the same error message, and when I click on it, I get the following description:
"There may be too few observation to consistently estimate the regression coefficients in a Mode B measurement model or extreme collinearity "
It would appear that groups (or subgroups) of less than 20 cases generate this error. I wanted to test whether the answers given by respondents where different according to their hierarchical position (1 stands for head of business unit, and 5 for operator at least 4 levels under head). As I have 2 sub-groups with only 16 and 20 cases, I had to take them both out for the analysis to run to the end. To be complete, I did 2 groups: both composed of two subgroups, but excluding the offending ones.
Can somebody explain why this is so and present some explanation as to how one can do?
Thank you.
"There may be too few observation to consistently estimate the regression coefficients in a Mode B measurement model or extreme collinearity "
It would appear that groups (or subgroups) of less than 20 cases generate this error. I wanted to test whether the answers given by respondents where different according to their hierarchical position (1 stands for head of business unit, and 5 for operator at least 4 levels under head). As I have 2 sub-groups with only 16 and 20 cases, I had to take them both out for the analysis to run to the end. To be complete, I did 2 groups: both composed of two subgroups, but excluding the offending ones.
Can somebody explain why this is so and present some explanation as to how one can do?
Thank you.
Xavier Brusset
Professor
Logistics and supply chain management
Toulouse Business School
Professor
Logistics and supply chain management
Toulouse Business School
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Re: Multigroup analyses
Your subgroups are simply too small. It is often not possible to estimate complex PLS models with only 16, 20, or 22 observations. And even if it would be possible the results would not be trustworthy. In your cases a multi-groups analysis is simply not possible unless you collect more data.
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
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de