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Regularized Generalized Canonical Correlation Analysis (RGCCA)

What is Regularized Generalized Canonical Correlation Analysis (RGCCA)? RGCCA is a method introduced by Tenenhaus et al. (2011). It allows to optimize a global function using an algorithm very similar to the PLSPM algorithm. Unlike the PLS approach, the results of the RGCCA are correlations between latent variables and between manifest variables and their associated latent variables (there is no regression...

Multicollinearity statistics

What is multicollinearity Variables are said to be multicollinear if there is a linear relationship between them. This is an extension of the simple case of collinearity between two variables. For example, for three variables X1, X2 and X3, we say that they are multicollinear if we can write: X1 = aX2 + bX3 where a and b are real numbers. How to detect multicollinearity To detect the multicolinearities...

k-means clustering

Description of the k-means clustering analysis in XLSTAT General description k-means clustering was introduced by McQueen in 1967. Other similar algorithms had been developed by Forgey (1965) (moving centers) and Friedman (1967). k-means clustering has the following advantages: An object may be assigned to a class during one iteration then change class in the following iteration, which is not possible...

DoE for choice based conjoint (CBC) analysis

Principle of design of experiments for choice based conjoint (CBC) analysis The principle of conjoint analysis is to present a set of products (also known as profiles) to the individuals who will note, class, or choose some of them. In an ideal analysis, individuals should test all possible products. But it is soon impossible; the capacity of each being limited and the number of combinations increases...

Dixon test for outliers

Principle of the test The Dixon test (1950, 1951, 1953), which is actually divided into six tests depending on the chosen statistic and on the number of outliers to identify, was developed to help determine if the greatest value or lowest value of a sample, or the two largest values, or the two smallest ones can be considered as outliers. This test assumes that the data correspond to a sample extracted...

Canonical Correspondence Analysis (CCA) tutorial

Consumer satisfaction analysis in Excel with PLSPM

Temporal Dominance of Sensations (TDS)

What is Temporal Dominance of Sensations (TDS)? Temporal Dominance of Sensations (TDS) is a temporal multidimensional sensory method (Pineau, Cordelle & Schlich, 2003). Panellists are presented with a list of attributes and asked to choose the dominant ones over consumption of the product. A dominant attribute is the most striking perception at a time, not necessarily the most intense one (Pineau...

Statistical Power for mean comparison

Statistical Power analysis for the comparison of means There are several tests to compare means, in XLSTAT we offer namely the t and z tests. XLSTAT allows estimating the power of these tests and calculates the number of observations required to obtain sufficient power. Power computations can also be applied for the Wilcoxon signed rank test and the Mann-Whitney test. When testing a hypothesis using...

Statistical Power for Cox model

Statistical Power for Cox model XLSTAT-Life Sciences offers a tool to apply the proportional hazards ratio Cox regression model. XLSTAT-Power estimates the power or calculates the necessary number of observations associated with this survival analysis model. What is Statistical Power for Cox model? What is Statistical Power? When testing a hypothesis on data using a statistical test, there are several...