The RDA, partial RDA and LDA parts are explained in terms of how the R functions work. Although this is useful, it is important that participants understand better how these methods work.
The level of detail can be discussed and adjusted, but it would be very helpful for participants to understand RDA from the perspective of a PCA done on the matrix predicted values of successive regressions of X on the variables in Y. The same should be applied to partial RDA, but adding the perspective from an RDA done on the residuals of regressions of X on W and on the residuals of Y on W.
This would be in alignment with previous discussions that there is abundant material online on how to use R functions, but that participants would benefit far more from the series through a more theoretical understanding of statistics.
The RDA, partial RDA and LDA parts are explained in terms of how the R functions work. Although this is useful, it is important that participants understand better how these methods work.
The level of detail can be discussed and adjusted, but it would be very helpful for participants to understand RDA from the perspective of a PCA done on the matrix predicted values of successive regressions of X on the variables in Y. The same should be applied to partial RDA, but adding the perspective from an RDA done on the residuals of regressions of X on W and on the residuals of Y on W.
This would be in alignment with previous discussions that there is abundant material online on how to use R functions, but that participants would benefit far more from the series through a more theoretical understanding of statistics.