Bartlett, M.S. (1937), “Properties of sufficiency and statistical tests,” Proceedings of the Royal Society of London Series A, 160, 268–282.

Bartlett, M.S. (1954), “A Note on the Multiplying Factors for Various Chi Square Approximations,” Journal of the Royal Statistical Society, 16 (Series B), 296-298.

Boulesteix, A.-L. and Strimmer, K. (2007), “Partial Least Squares: A Versatile Tool for the Analysis of High-Dimensional Genomic Data,” Briefings in Bioinformatics, 8(1), 32-44.

Cox, I. and Gaudard, M. (2013), Discovering Partial Least Squares with JMP, Cary NC: SAS Institute Inc.

Cronbach, L.J. (1951), “Coefficient Alpha and the Internal Structure of Tests,” Psychometrika, 16, 297–334.

De Jong, S. (1993), “SIMPLS: An Alternative Approach to Partial Least Squares Regression,” Chemometrics and Intelligent Laboratory Systems, 18, 251–263.

Denham, M.C. (1997), “Prediction Intervals in Partial Least Squares,” Journal of Chemometrics, 11, 39-52.

Dwass, M. (1955), “A Note on Simultaneous Confidence Intervals,” Annals of Mathematical Statistics 26: 146–147.

Eriksson, L., Johansson, E., Kettaneh-Wold, N., Trygg, J., Wikstrom, C., and Wold, S. (2006), Multi- and Megavariate Data Analysis Basic Principles and Applications (Part I), Chapter 4, Umetrics.

Farebrother, R.W. (1981), “Mechanical Representations of the L1 and L2 Estimation Problems,” Statistical Data Analysis, 2nd Edition, Amsterdam, North Holland: edited by Y. Dodge.

Fieller, E.C. (1954), “Some Problems in Interval Estimation,” Journal of the Royal Statistical Society, Series B, 16, 175-185.

Florek, K., Lukaszewicz, J., Perkal, J., and Zubrzycki, S. (1951a), “Sur La Liaison et la Division des Points d’un Ensemble Fini,” Colloquium Mathematicae, 2, 282–285.

Garthwaite, P. (1994), “An Interpretation of Partial Least Squares,” Journal of the American Statistical Association, 89:425, 122-127.

Golub, G.H., Kahan, W. (1965), “Calculating the singular values and pseudo-inverse of a matrix,” Journal of the Society for Industrial and Applied Mathematics: Series B, Numerical Analysis 2:2, 205–224.

Goodnight, J.H. (1978), “Tests of Hypotheses in Fixed Effects Linear Models,” SAS Technical Report R–101, Cary NC: SAS Institute Inc, also in Communications in Statistics (1980), A9 167–180.

Goodnight, J.H. and W.R. Harvey (1978), “Least Square Means in the Fixed Effect General Linear Model,” SAS Technical Report R–103, Cary NC: SAS Institute Inc.

Harris, C.W. and Kaiser, H.F. (1964), “Oblique Factor Analytic Solutions by Orthogonal Transformation,” Psychometrika, 32, 363–379.

Hartigan, J.A. (1981), “Consistence of Single Linkage for High–Density Clusters,” Journal of the American Statistical Association, 76, 388–394.

Hocking, R.R. (1985), The Analysis of Linear Models, Monterey: Brooks–Cole.

Hoskuldsson, A. (1988), “PLS Regression Methods,” Journal of Chemometrics, 2:3, 211-228.

Huber, P.J. (1964), “Robust Estimation of a Location Parameter,” Annals of Mathematical Statistics, 35:1, 73-101.

Huber, Peter J. (1973), “Robust Regression: Asymptotics, Conjecture, and Monte Carlo,” Annals of Statistics, Volume 1, Number 5, 799-821.

Huber, P.J. and Ronchetti, E.M. (2009), Robust Statistics, Second Edition, Wiley.

Jackson, J. Edward (2003), A User’s Guide to Principal Components, New Jersey: John Wiley and Sons.

Jardine, N. and Sibson, R. (1971), Mathematical Taxonomy, New York: John Wiley and Sons.

Lindberg, W., Persson, J.-A., and Wold, S. (1983), “Partial Least-Squares Method for Spectrofluorimetric Analysis of Mixtures of Humic Acid and Ligninsulfonate,” Analytical Chemistry, 55, 643–648.

Mason, R.L. and Young, J.C. (2002), Multivariate Statistical Process Control with Industrial Applications, Philadelphia: ASA-SIAM.

McLachlan, G.J. and Krishnan, T. (1997), The EM Algorithm and Extensions, New York: John Wiley and Sons.

McQuitty, L.L. (1957), “Elementary Linkage Analysis for Isolating Orthogonal and Oblique Types and Typal Relevancies,” Educational and Psychological Measurement, 17, 207–229.

Milligan, G.W. (1980), “An Examination of the Effect of Six Types of Error Perturbation on Fifteen Clustering Algorithms,” Psychometrika, 45, 325–342.

Nelson, Philip R.C., Taylor, Paul A., MacGregor, John F. (1996), “Missing Data Methods in PCA and PLS: Score calculations with incomplete observations,” Chemometrics and Intelligent Laboratory Systems, 35, 45-65.

Press, W.H, Teukolsky, S.A., Vetterling, W.T., Flannery, B.P. (1998), Numerical Recipes in C: The Art of Scientific Computing, Second Edition, Cambridge, England: Cambridge University Press.

SAS Institute Inc. (2011), SAS/STAT 9.2 User’s Guide, “The VARCLUS Procedure,” Cary, NC: SAS Institute Inc. Retrieved April 15, 2015 from http://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#varclus_toc.htm.

SAS Institute Inc. (2011), SAS/STAT 9.3 User’s Guide, “The PLS Procedure,” Cary, NC: SAS Institute Inc. Retrieved April 15, 2015 from http://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#pls_toc.htm.

SAS Institute Inc. (2011), SAS/STAT 9.3 User’s Guide, “The CANDISC Procedure,” Cary, NC: SAS Institute Inc. Retrieved April 15, 2015 from http://support.sas.com/documentation/cdl/en/statug/63962/HTML/default/viewer.htm#candisc_toc.htm.

Sneath, P.H.A. (1957) “The Application of Computers to Taxonomy,” Journal of General Microbiology,17, 201–226.

Sokal, R.R. and Michener, C.D. (1958), “A Statistical Method for Evaluating Systematic Relationships,” University of Kansas Science Bulletin, 38, 1409–1438.

Tobias, R.D. (1995), “An Introduction to Partial Least Squares Regression,” Proceedings of the Twentieth Annual SAS Users Group International Conference, Cary, NC: SAS Institute Inc.

Tracy, N.D., Young, J.C., Mason, R.R. (1992), “Multivariate Control Charts for Individual Observations,” Journal of Quality Technology, 24, 88–95.

Umetrics (1995), Multivariate Analysis (3-day course), Winchester, MA.

Wold, (1980), “Soft Modelling: Intermediate between Traditional Model Building and Data Analysis,” Mathematical Statistics (Banach Center Publications, Warsaw), 6, 333-346.

Wold, S. (1994), “PLS for Multivariate Linear Modeling”, QSAR: Chemometric Methods in Molecular Design. Methods and Principles in Medicinal Chemistry.

Wold, S., Sjostrom, M., and Eriksson, L. (2001), “PLS-Regression: A Basic Tool of Chemometrics,” Chemometrics and Intelligent Laboratory Systems, 58:2, 109-130.

Wright, S.P. and R.G. O’Brien (1988), “Power Analysis in an Enhanced GLM Procedure: What it Might Look Like,” SUGI 1988, Proceedings of the Thirteenth Annual Conference, 1097–1102, Cary NC: SAS Institute Inc.