- Yaffe, Kristine;
- Hunt, MJO;
- Weissfeld, L;
- Boudreau, RM;
- Aizenstein, H;
- Newman, AB;
- Simonsick, EM;
- Van, DR;
- Thomas, F;
- Rosano, C
When data are sparse and/or predictors multicollinear, current implementation of sparse partial least squares (SPLS) does not give estimates for non-selected predictors nor provide a measure of inference. In response, an approach termed "all-possible" SPLS