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Partial Least Squares Modeling in Research on Educational Achievement

Partial Least Squares Modeling in Research on Educational Achievement

This paper contains a discussion of partial least squares (PLS) path modeling with latent
+ q% F! Q% U/ p9 z, X# Lspss论坛|spss下载|spss视频|Amos|SEM|SAS|Matlab|Eviewsconstructs as a general method for research on educational achievement. To the extent thatspsschina.cn# d1 F( V* i6 _* r+ n- F* ?
such research requires the analysis of comparatively large and complex models under mild
& d1 C8 X' K) x& H! x+ y: lsupplementary assumptions, PLS is an extremely flexible and powerful tool for statistical
; ?9 \7 u* G0 g. @- f% Mspss论坛|spss下载|spss视频|Amos|SEM|SAS|Matlab|Eviewsmodel building. The formal specification, estimation, and evaluation of PLS models isspsschina.cn  ~- \. y. V3 E9 j, }
described with special emphasis on the features that distinguish PLS from other methods for
3 Y* Z" k" u+ I( |" N" Npath analysis. This specifically concerns distribution-free least squares estimation andspss论坛|spss下载|spss视频|Amos|SEM|SAS|Matlab|Eviews- P/ Q7 H- I) L( X
distribution-free model evaluation using jackknife techniques.

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2009-6-29 00:21, 下载次数: 5

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