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<p class=MsoNormal>Dear colleagues:<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Version 3.0 of WarpPLS is now available! You can download
and install it for a free 90-day trial from:<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>http://warppls.com<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>The full User Manual is also available for download from the
web site above separately from the software.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Some important notes for users of previous versions:<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Version 2.0 users can use the same license information
that they already have; it will work for version 3.0 for the remainder of their
license periods.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Project files generated with previous versions are
automatically converted to version 3.0 project files. Users are notified of
that by the software, and given the opportunity not to convert the files if
they so wish.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- The MATLAB Compiler Runtime 7.14, used in this version, is
the same as the one used in version 2.0. Therefore, if you already have WarpPLS
2.0 installed on your computer, you should uncheck the Runtime component on the
installer (i.e., the self-installing .exe file). The same Runtime cannot be
installed twice on the same computer.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>WarpPLS is a powerful PLS-based structural equation modeling
(SEM) software. Since its first release in 2009, its user base has grown
steadily, with more than 5,000 users worldwide today.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Some of its most distinguishing features are the following:<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- It is easy to use, with a step-by-step user interface
guide.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- It identifies nonlinear relationships, and estimates path
coefficients accordingly. <o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- It also models linear relationships, using a standard PLS
regression algorithm.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- It models reflective and formative variables, as well as
moderating effects.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- It calculates P values, model fit indices, and
collinearity estimates.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Below is a list of new features in this version. The User
Manual has more details on how these new features can be useful in SEM
analyses.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Addition of latent variables as indicators. Users now have
the option of adding latent variable scores to the set of standardized
indicators used in an SEM analysis.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Blindfolding. Users now have the option of using a third
resampling algorithm, namely blindfolding, in addition to bootstrapping and
jackknifing.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Effect sizes. Cohen’s f-squared effect size
coefficients are now calculated and shown for all path coefficients.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Estimated collinearity. Collinearity is now estimated
before the SEM analysis is run. When collinearity appears to be too high, users
are warned about it.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Full collinearity VIFs. VIFs are now shown for all latent
variables, separately from the VIFs calculated for predictor latent variables in
individual latent variable blocks.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Indirect and total effects. Indirect and total effects are
now calculated and shown, together with the corresponding P values, standard
errors, and effect sizes.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- P values for all weights and loadings. P values are now
shown for all weights and loadings, including those associated with indicators
that make up moderating variables.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Predictive validity. Stone-Geisser Q-squared coefficients
are now calculated and shown for each endogenous variable in an SEM model.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Ranked data. Users can now select an option to conduct
their analyses with only ranked data, whereby all the data is automatically
ranked prior to the SEM analysis (the original data is retained in unranked
format).<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Restricted ranges. Users can now run their analyses with
subsamples defined by a range restriction variable, which may be standardized
or unstandardized.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- Standard errors for all weights and loadings. Standard
errors are now shown for all loadings and weights.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>- VIFs for all indicators. VIFs are now shown for all
indicators, including those associated with moderating latent variables.<o:p></o:p></p>
<p class=MsoNormal><o:p> </o:p></p>
<p class=MsoNormal>Enjoy!<o:p></o:p></p>
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