To predict the Overall Liking resulted from decreasing the percentages of Too Weak or Too Strong. This method would help clients in prioritizing sensory aspects to improve.

The Nash-Sutcliffe efficiency , Willmott's index and Model Performance Index (MPI) are suitable indices to add XLSTAT for assessing model performance.

Would be nice to be able to integrate the area under the curve in linear and non-linear models.

I think XLSTAT provides partial least squares models but not general least squares. This would be very practical for time series analysis, for instance.

Spatial Autocorrelation Indices (e.g Moran's I) are mainstream of spatial statistics that are worth being implemented in XLSTAT software. They are useful for ecological studies.

Detrended Correspondence Analysis (DCA) is a popular multivariate analysis tool that is widely used to explore potentially sparse community data matrices in ecology. It is usually able to remove undesired arch effects.

Introduction of kernel functions in PLS can significantly improve the explanatory power of regression. Hope it comes true in future.

In a linear hierarchy regression, it is important to know the change in R-squared to know if additional variables in a model increase the association with the predictor variables between the models (independent variables).

important to know how many subjects are at risk at each major time interval. I have to look this up in the table and add it manually for each group being analyzed.

Hello XLSTAT team. Any plans to add the eta squared and partial eta squared for ANOVA and regression ? These measures are commonly used to study the effect size. Plus, it is easy to implement and straightforward to interpret !