Low R square value

Frequently asked questions about PLS path modeling.
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Real name and title: shekhu

Low R square value

Post by rathor1072@gmail.com » Mon Jan 06, 2020 1:00 pm

How can I explain low R square value? Is there any paper/book I can refer for explanation ?

Thank you

SmartPLS Developer
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Real name and title: Dr. Jan-Michael Becker

Re: Low R square value

Post by jmbecker » Mon Jan 20, 2020 8:54 am

Low R² means that you are not able to explain much variance in your dependent variable.
That can have several reasons. For example, your DV is very noisy (i.e., has a lot of variance). This may be because of error variance or because of many things contribute to the DV and your predictor is only one of many. Maybe you need to control for more other influences? Your predictor may also simply not be a (good) predictor of the DV; etc.

Generally, the expected R² level strongly depends on the context and the field of study. If you have a customer satisfaction model (which is well researched) and you control for the most important known influences (image, quality, expectations, etc.) you should expect R² > 60%. However, if you are in consumer behavior and want to explain some real behavior by some specific intervention (e.g., treatment vs. no treatment) it is rather common to expect R² in the range of 10% - 20% or even less.
Dr. Jan-Michael Becker, University of Cologne, SmartPLS Developer
Researchgate: https://www.researchgate.net/profile/Jan_Michael_Becker
GoogleScholar: http://scholar.google.de/citations?user ... AAAJ&hl=de

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