Tuesday, September 13, 2016
Advantages of nonlinear over segmentation analyses in path models
Nonlinear analyses employing the software WarpPLS allow for the identification of linear segments emerging from a nonlinear analysis, but without the need to generate subsamples. A new article is available demonstrating the advantages of nonlinear over data segmentation analyses. These include a larger overall sample size for calculation of P values, and the ability to uncover very high segment-specific path coefficients. Its reference, abstract, and link to full text are available below.
Kock, N. (2016). Advantages of nonlinear over segmentation analyses in path models. International Journal of e-Collaboration, 12(4), 1-6.
The recent availability of software tools for nonlinear path analyses, such as WarpPLS, enables e-collaboration researchers to take nonlinearity into consideration when estimating coefficients of association among linked variables. Nonlinear path analyses can be applied to models with or without latent variables, and provide advantages over data segmentation analyses, including those employing finite mixture segmentation techniques (a.k.a. FIMIX). The latter assume that data can be successfully segmented into subsamples, which are then analyzed with linear algorithms. Nonlinear analyses employing WarpPLS also allow for the identification of linear segments mirroring underlying nonlinear relationships, but without the need to generate subsamples. We demonstrate the advantages of nonlinear over data segmentation analyses.
Among other things this article shows that identification of linear segments emerging from a nonlinear analysis with WarpPLS allows for: (a) a larger overall sample size for calculation of P values, which enables researchers to uncover actual segment-specific effects that could otherwise be rendered non-significant due to a combination of underestimated path coefficients and small subsample sizes; and (b) the ability to uncover very high segment-specific path coefficients, which could otherwise be grossly underestimated.
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9 comments:
Dear Prof. kock
Can we check for Endogeneity issues with WarpPLS?
Many thanks
Regards
Yes, starting in version 6.0 of WarpPLS. See the link below:
http://bit.ly/2rF96Hu
Dear Prof. Dr Kock,
Can we use WarpPLS to analyse secondary data for a single period (one year)?
Thank you so much.
Best regards
Kevin
Hi Kevin. Yes, you can.
Thank you for your prompt response Prof. Dr Kock. I will definitely going to learn using it for my upcoming research. Have a great day and stay safe.
Best regards
Kevin
Dear Prof. Dr. Kock,
Greetings from Malaysia, I hope all is well with you.
I have run analysis on my data (secondary). The results in my Reflective measurement model show that the cronbach's alpha and Composite Reliability (CR) are equal to 1 because I am using single question. Would that be a problem?
For your information Prof. I am measuring internet financial reporting quality (dependent variable) which is formed by several constructs. Nevertheless, results show that several of my indicator of variable were insignificant. Based on your literature, these insignificant variables need to be deleted. Would that be necessary since these constructs are needed to form the internet financial reporting quality?
I look forward to hearing from you soon. Thank you so much for kind guidance and stay safe Prof. Dr. Kock.
Best regards
Kevin
Hi Kevin. Generally this would lead to an underestimation of the path coefficients associated with the LV, with the ultimate result that your test would yield more conservative results - it would have lower power.
Hi Prof. Dr. Kock,
Hope all is well with you. As per our previous discussion on my analysis results showing that composite reliability (CR) and average variance extracted (AVE) all equal to '1", you are suggesting this would lead to underestimation of the path coefficient with LV, thereby yielding conservative results. Given that the results are conservative in nature, would it be wise for me to report the results in the thesis? or should I run another test? Do you have any suggestions on how should I address this matter. Thank you so much Professor Kock for your kind guidance. I look forward to hearing from you soon. Take care and stay safe.
Best regards
Kevin
Hi Kevin. What do the members of your committee think?
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