When I check or uncheck different constructs in the blindfolding procedure (in a former discussion someone told this feature is not connected in M3) differ the results...!?
Wich constructs must be checked?
different blindfolding results by checking diff. constructs
-
cringle
- SmartPLS Developer
- Posts: 818
- Joined: Tue Sep 20, 2005 9:13 am
- Real name and title: Prof. Dr. Christian M. Ringle
- Location: Hamburg (Germany)
- Contact:
Hi,
the checkbox window of the blindfolding procedure has not been correctly "wired" to the underlying blindfolding algorithm in the current version of SmartPLS. We already corrected our experimental versions and will fix this problem in the next SmartPLS release.
As a consequence, the Martin's observation is correct. Checking and unchecking boxes changes the order variables in the underlying data matrix and, thus, the blindfolding outcomes.
Work-around:
SmartPLS always provides correct blindfolding outcomes if you analyze only one latent variable at the time.
For example, you have two latent exogenous variables (LV1 and LV2) and one latent endogenous variable (LV3). The SmartPLS blindfolding results are identical to the LVPLS software,
1. for the cv-redundancy of LV3, if you check only the specific endogenous LV under analysis (LV3);
2. for the cv-communality of LV3, if you check all other LVs in the model (LV1 and LV2 and not LV 3) to obtain the results for LV3.
Cheers,
Christian
the checkbox window of the blindfolding procedure has not been correctly "wired" to the underlying blindfolding algorithm in the current version of SmartPLS. We already corrected our experimental versions and will fix this problem in the next SmartPLS release.
As a consequence, the Martin's observation is correct. Checking and unchecking boxes changes the order variables in the underlying data matrix and, thus, the blindfolding outcomes.
Work-around:
SmartPLS always provides correct blindfolding outcomes if you analyze only one latent variable at the time.
For example, you have two latent exogenous variables (LV1 and LV2) and one latent endogenous variable (LV3). The SmartPLS blindfolding results are identical to the LVPLS software,
1. for the cv-redundancy of LV3, if you check only the specific endogenous LV under analysis (LV3);
2. for the cv-communality of LV3, if you check all other LVs in the model (LV1 and LV2 and not LV 3) to obtain the results for LV3.
Cheers,
Christian
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
CV Communality for more than 1 endogenous constructs
Hi,
Suppose we have a model with 2 endogenous constructs - L1,L2 wherein L1 leads to L2 and 9 exogenous constructs - L3 to L11. For finding the CV - Communality of L2, should we select L1 also along with the 9 exogenous variables.
Thanks,
Nitin
Suppose we have a model with 2 endogenous constructs - L1,L2 wherein L1 leads to L2 and 9 exogenous constructs - L3 to L11. For finding the CV - Communality of L2, should we select L1 also along with the 9 exogenous variables.
Thanks,
Nitin
-
cringle
- SmartPLS Developer
- Posts: 818
- Joined: Tue Sep 20, 2005 9:13 am
- Real name and title: Prof. Dr. Christian M. Ringle
- Location: Hamburg (Germany)
- Contact:
Hi,
yes. Just check each latent variable variable one by one and use the selection scheme which I provided.
Cheers
Christian
yes. Just check each latent variable variable one by one and use the selection scheme which I provided.
Cheers
Christian
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
CV Communality for more than 1 endogenous constructs
Hi Dr. Ringle,
Thanks for your prompt reply.
Thanks,
Nitin
Thanks for your prompt reply.
Thanks,
Nitin
Q^2 excluded
excuse me guys,
I have two questions about Q^2 excluded :
1.
I designed a model as follows: (Model Attached)
I can not calculate Q^2 excluded for job satisfaction construct (Job Satisf in model, CV.Red included for Job Satisfaction = 0.296), when I remove the link between Islamic ethics (Islamic Eth in model) and job satisfaction constructs, SmartPLS not present any CV.Red for job satisfaction in the ouputs (However, it seemed logical). but in Outline a CV.RED displayed for job satisfaction that is equal with CV.Com (0.486) of Job Satisfaction. Nevertheless, how much should I consider for Q ^ 2 excluded & is there possible to calculate q ^ 2 for job satisfaction?
2. In one model, is it possible that f ^ 2 large and q^2 small? If this happens, how it is interpreted? in The first question, if we consider 0.486 as Q ^ 2 excluded, the value of q ^ 2 is small and given the values of R ^ 2 (R^2 included=0.40, R^2 excluded=0), f ^ 2 value is large.
I would be very grateful if you tell me the above.
I have two questions about Q^2 excluded :
1.
I designed a model as follows: (Model Attached)
I can not calculate Q^2 excluded for job satisfaction construct (Job Satisf in model, CV.Red included for Job Satisfaction = 0.296), when I remove the link between Islamic ethics (Islamic Eth in model) and job satisfaction constructs, SmartPLS not present any CV.Red for job satisfaction in the ouputs (However, it seemed logical). but in Outline a CV.RED displayed for job satisfaction that is equal with CV.Com (0.486) of Job Satisfaction. Nevertheless, how much should I consider for Q ^ 2 excluded & is there possible to calculate q ^ 2 for job satisfaction?
2. In one model, is it possible that f ^ 2 large and q^2 small? If this happens, how it is interpreted? in The first question, if we consider 0.486 as Q ^ 2 excluded, the value of q ^ 2 is small and given the values of R ^ 2 (R^2 included=0.40, R^2 excluded=0), f ^ 2 value is large.
I would be very grateful if you tell me the above.
-
Hengkov
- PLS Super-Expert
- Posts: 1599
- Joined: Sun Apr 24, 2011 10:13 am
- Real name and title: Hengky Latan
- Location: AMQ, Indonesia
- Contact:
Re: different blindfolding results by checking diff. constru
Hi,
First, you must understand that Q^2 and q^2 can not be calculated with the formula if there is only one independent variable. Thus, the value of Q^2 and q^2 will be equal to the value of R^2 of the dependent variables (job satisfaction).
Secondly, Yes of course possible value of f^2 will be different between the predictor variables affect the dependent variabe; so it would be logical to explain the role of each variable to DVs.
Greetings,
First, you must understand that Q^2 and q^2 can not be calculated with the formula if there is only one independent variable. Thus, the value of Q^2 and q^2 will be equal to the value of R^2 of the dependent variables (job satisfaction).
Secondly, Yes of course possible value of f^2 will be different between the predictor variables affect the dependent variabe; so it would be logical to explain the role of each variable to DVs.
Greetings,