Factor Analysis as a Statistical Method.

By J. Thornby, D. Lawley, A. E. Maxwell. 1964

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Citations in the corpus

Principal Components and Regularized Estimation of Factor Models (2017, background): “Under the assumption that T tends to inﬁnity with N ﬁxed, Anderson and Rubin (1956), Joreskog (1967), and Lawley and Maxwell (1971) show that the factor loadings estimated by maximum likelihood or covariance structure methods are √ T consistent and asymptotically normal.”
Cognitive abilities - aspects of structure, process and measurement (2000, methodology): “The regression method of Lawley and Maxwell (1963) was applied.”
The Measurement Equivalence of Web-Based and Paper-and-Pencil Measures of Transformational Leadership (2006, background): “Alternative options for dealing with the offending estimate include removing items (Lawley & Maxwell, 1971) and setting the residual variance to zero or some other small value (Chen et al., 2001).”
Generating Criteria for Measuring Teacher Effectiveness Through a Self-Evaluation Approach: A Complementary Way of Measuring Teacher Effectiveness (2002, methodology): “Moreover, varimax rotation procedure was used since it is the most common of the orthogonal rotation methods (Kline, 1994; Maxwell & Lawley, 1971) and transforms the initial factor matrix into one that is easier to interpret.”
Estimation of oblique structure via penalized likelihood factor analysis (2013, methodology): “s because of overparametrization (e.g., Akaike 1987). In particular, the commonly-used algorithms for maximum likelihood factor analysis (e.g., Joreskog 1967; Jennrich and Robinson 1969; Clarke 1970; Lawley and Maxwell 1971) cannot often be applied when the number of variables is larger than the num”
Maximum likelihood from incomplete data via the EM - algorithm plus discussions on the paper (1977, methodology): “The J6reskog algorithm described in Lawley and Maxwell (1971) is specifically designed to handle such problems, while it appears that the version of the EM algorithm outlined in Section 4.7 may be stopped long before a Heywood case can be recognized.”
Principal components estimation and identification of static factors (2013, methodology): “Thus we need at least r 2 restrictions in order to identity F and Λ, see Lawley and Maxwell (1971).”
Identification and Estimation of Dynamic Factor Models (2012, background): “Classical factor analysis (e.g., Anderson and Rubin (1956), or Lawley and Maxwell (1971)) focuses on static factor models.”