Discriminant validity
Thanks for your comments.
I did and I performed the new analysis. However, one of my latent variables got the value of AVE and Cronbachs Alpha 1.000000? This item had two questions in questionnaire, which I deleted one of them as you said. Is this Confirmatory factor analysis?
Do I need to report the deleted items?
Last but not least, two other constructs Cronbachs decreased to below .70 ! Do I need to remove them? But these are new constructs and they are important to keep!!!!
This is a new model that I am proposing, but the questions are based on different valid questionnaires.
I did and I performed the new analysis. However, one of my latent variables got the value of AVE and Cronbachs Alpha 1.000000? This item had two questions in questionnaire, which I deleted one of them as you said. Is this Confirmatory factor analysis?
Do I need to report the deleted items?
Last but not least, two other constructs Cronbachs decreased to below .70 ! Do I need to remove them? But these are new constructs and they are important to keep!!!!
This is a new model that I am proposing, but the questions are based on different valid questionnaires.
Mahmood
Hi Mahmood,
With a Cronbach's alpha of ,27 the reliability of the Variable (IV or DV) is too low. This would have been the case in SmartPLS and in SPSS, so you'll have to look at how the questions in the questionnaire predict the variable. Were they translated correctly, are they clear enough, do they measure the same variable etc etc. Also multivariate approaches (e.g. factor analysis) may be helpful.
Good luck,
Dennis
With a Cronbach's alpha of ,27 the reliability of the Variable (IV or DV) is too low. This would have been the case in SmartPLS and in SPSS, so you'll have to look at how the questions in the questionnaire predict the variable. Were they translated correctly, are they clear enough, do they measure the same variable etc etc. Also multivariate approaches (e.g. factor analysis) may be helpful.
Good luck,
Dennis
- Hengkov
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Hi, Mahmood.
Your result AVE and Cronbach's Alpha is 1.000? You questionnaire used likert scale?
For your construct some literature suggest used > 3 items- 6 items measures.
Cronbach's Alpha PLS under estimate used Dillon Goldenstein.
For report please see Chin, W.W. (2010) How to Write up PLS Analysis. Handbook PLS, Berlin-Spinger.
Hi, Zhang.
Rule of Thumb square root average variance extracted > correlation.
For your case equal => acceptable, if cross loadings > 0.70 and indicator's loadings should be higher than all of its cross loadings.
Regards,
Hengky.
Your result AVE and Cronbach's Alpha is 1.000? You questionnaire used likert scale?
For your construct some literature suggest used > 3 items- 6 items measures.
Cronbach's Alpha PLS under estimate used Dillon Goldenstein.
For report please see Chin, W.W. (2010) How to Write up PLS Analysis. Handbook PLS, Berlin-Spinger.
Hi, Zhang.
Rule of Thumb square root average variance extracted > correlation.
For your case equal => acceptable, if cross loadings > 0.70 and indicator's loadings should be higher than all of its cross loadings.
Regards,
Hengky.
Re: About AVE
Hi Zhang,
Good luck,
Dennis
In addition to Hengky's post, I would investigate your data for multicollinearity. See a.o. Field, A.P. (2010) Discovering Statistics Using SPSS, Los Angeles, CA: Sage.mzhang wrote:What is one of my AVE is about equal to one of the correlation?
Is this ok?
Good luck,
Dennis
I dropped the items with less than 0.70 ( outer loading) and the Cronbachs Alpha as well as AWE of this construct changed to 1.00000. why it is 1?Hengkov wrote:Hi, Mahmood.
Your result AVE and Cronbach's Alpha is 1.000? You questionnaire used likert scale?
For your construct some literature suggest used > 3 items- 6 items measures.
Cronbach's Alpha PLS under estimate used Dillon Goldenstein.
For report please see Chin, W.W. (2010) How to Write up PLS Analysis. Handbook PLS, Berlin-Spinger.
Hi, Zhang.
Rule of Thumb square root average variance extracted > correlation.
For your case equal => acceptable, if cross loadings > 0.70 and indicator's loadings should be higher than all of its cross loadings.
Regards,
Hengky.
This is the construct that has the Cronbachs 0.22 before I drop that items.
Thanks for your help.
Mahmood
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Hi Mahmood,
Your construct in model reflective or formative?
If formative, you not assess validity and reliability construct (loading factor, AVE, Cronbach Alpha etc), but you look significant weight.
For you result AVE = 1, please check problem collonierity.
You items used likert scale, dichotomus, or?
Cronbach Alpha PLS under estimate, look composite reliability (if reflective model).
Best Regards,
Hengky
Your construct in model reflective or formative?
If formative, you not assess validity and reliability construct (loading factor, AVE, Cronbach Alpha etc), but you look significant weight.
For you result AVE = 1, please check problem collonierity.
You items used likert scale, dichotomus, or?
Cronbach Alpha PLS under estimate, look composite reliability (if reflective model).
Best Regards,
Hengky
Thanks for your help.Hengkov wrote:Hi Mahmood,
Your construct in model reflective or formative?
If formative, you not assess validity and reliability construct (loading factor, AVE, Cronbach Alpha etc), but you look significant weight.
For you result AVE = 1, please check problem collonierity.
You items used likert scale, dichotomus, or?
Cronbach Alpha PLS under estimate, look composite reliability (if reflective model).
Best Regards,
Hengky
May I ask you to have a look at the overall quality of this study? I added the image of boots raping and PLS here in this link:
http://www.hajili.com/uncategorised/pls-algorithm
Mahmood
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Hi Mahmood,
I'm look your result model, you drop only indicator FC1 (Social Commerce Components) => model fit. For another construct with loading factor > 0.50 acceptable (see Chin 1998), because your indicator construct only 2, 3 and 4 (can't delete). Recomendation some literature for measures construct (indicators 5-6 items).
Chin, W. W. 1998. The partial least squares approach for structural equation modeling. in G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-236). London: Lawrence Erlbaum Associates.
Regards,
Hengky
I'm look your result model, you drop only indicator FC1 (Social Commerce Components) => model fit. For another construct with loading factor > 0.50 acceptable (see Chin 1998), because your indicator construct only 2, 3 and 4 (can't delete). Recomendation some literature for measures construct (indicators 5-6 items).
Chin, W. W. 1998. The partial least squares approach for structural equation modeling. in G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-236). London: Lawrence Erlbaum Associates.
Regards,
Hengky
Thanks for your comment.Hengkov wrote:Hi Mahmood,
I'm look your result model, you drop only indicator FC1 (Social Commerce Components) => model fit. For another construct with loading factor > 0.50 acceptable (see Chin 1998), because your indicator construct only 2, 3 and 4 (can't delete). Recomendation some literature for measures construct (indicators 5-6 items).
Chin, W. W. 1998. The partial least squares approach for structural equation modeling. in G. A. Marcoulides (Ed.), Modern methods for business research (pp. 295-236). London: Lawrence Erlbaum Associates.
Regards,
Hengky
Shall I drop FC1 and do PLS algorithm and Bootsraping again and show the new results in my paper?
Mahmood
Thanks again.Hengkov wrote:Hi Mahmood,
Your construct in model reflective or formative?
If formative, you not assess validity and reliability construct (loading factor, AVE, Cronbach Alpha etc), but you look significant weight.
For you result AVE = 1, please check problem collonierity.
You items used likert scale, dichotomus, or?
Cronbach Alpha PLS under estimate, look composite reliability (if reflective model).
Best Regards,
Hengky
So, for the dependent variable or formative construct, I don’t need the questionnaire items. Do I?
As I read the papers I don’t see they measure the formative construct .
If not how can I see the R square on that?
I am designing a new model now.
Mahmood