Abstract
The aim of this chapter is to describe the context of some of the earliest applications of partial least squares in the analysis of large-scale school survey data. In the late 1960s, several large school surveys had been conducted, but the analytical methods available at the time were not capable of reflecting structural equation models covering these large data sets. Instead analysis proceeded more by analogical models than structural equation models. Such models had very limited usefulness for addressing significant policy issues. The development of partial least squares and its application in school survey research led not only to findings more relevant to policy issues of concern but also supported the development of the underlying theoretical models.
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Notes
- 1.
Note that although the tables reported the correlations and regression coefficients for conceptually distinct groups of variables, the regression equations yielding those regression coefficients included all 24 predictor variables. On negative contributions to variance explained, see Note on Commonality Analysis at the end of this chapter.
- 2.
Commonality analysis was developed within the framework of the early large-scale surveys described in this chapter but is not widely used today. See Note on Commonality Analysis at the end of this chapter.
- 3.
This was a first and informal step toward the use of hierarchically structured latent variables within the NIPALS/PLS framework. There were two levels of latent variables. The “lower level” latent variables were formed using principal component weights. The resulting compounds were then treated as manifest variables in the usual manner.
- 4.
Unlimited in principle, in practice limited by the maximum memory space allowed by the IBM mainframe computer we used, but never a problem in our analyses. This program was later developed to include hierarchically structured latent variables as a standard PLS option. The program was written in FORTRAN IV, later FORTRAN G, and comprised some 1500 lines of code. Around the same time, Lohmöller was writing his program (see Lohmöller 1989), which became the basis from which the most commonly used program today has evolved.
- 5.
Ceteris paribus: Latin. Other things being equal, holding other things constant
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Noonan, R. (2017). Partial Least Squares: The Gestation Period. In: Latan, H., Noonan, R. (eds) Partial Least Squares Path Modeling. Springer, Cham. https://doi.org/10.1007/978-3-319-64069-3_1
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