A frequent criticism of exploratory factor analysis (EFA) is that it does not allow correlated residuals to be modelled, while they can be routinely specified in the confirmatory (CFA) model. In this article, we propose an EFA approach in which both the common factor solution and the residual matrix are unrestricted (i.e., the correlated residuals…

Generalized structured component analysis (GSCA) is a multivariate method for specifying and examining interrelationships between observed variables and components. Despite its data-analytic flexibility honed over the decade, GSCA always defines every component as a linear function of observed variables, which can be less optimal when observed…

Linear functional relationships are intended to be symmetric and therefore cannot generally be accurately estimated using ordinary least squares regression equations. Orthogonal regression (OR) models allow for errors in both "Y" and "X" and therefore can provide symmetric estimates of these relationships. The most…

Ordinary least squares (OLS) regression and orthogonal regression (OR) address different questions and make different assumptions about errors. The OLS regression of Y on X yields predictions of a dependent variable (Y) contingent on an independent variable (X) and minimizes the sum of squared errors of prediction. It assumes that the independent…

Recently, studies have adopted fixed effects modeling to identify the returns to college. This method has the advantage over ordinary least squares estimates in that unobservable, individual-level characteristics that may bias the estimated returns are differenced out. But the method requires extensive longitudinal data and involves complex…

Various studies show that higher education institutions contribute to regional economic development by R&D, creation of human capital, knowledge and technology transfer, and by creation of a favourable milieu. It is brought out that the basic procedure is to sum expenditures of the college community (students, faculty, staff and visitors)…

Budgetary constraints on the public purse have led Australian Federal and State governments to focus increasingly on the efficiency of public institutions, including Technical and Further Education (TAFE) institutes. In this study, we define efficiency as the relationship between financial and administrative inputs and educational outputs. We…

It is often difficult and costly to obtain individual-level student achievement data, yet, researchers are frequently reluctant to use school-level achievement data that are widely available from state websites. We argue that public-use aggregate school-level achievement data are, in fact, sufficient to address a wide range of evaluation questions…

The proposed paper studies the bias in the two-stage least squares, or 2SLS, estimator that is caused by the compliance-effect covariance (hereafter, the compliance-effect bias). It starts by deriving the formula for the bias in an infinite sample (i.e., in the absence of finite sample bias) under different circumstances. Specifically, it…

We update theories of teacher expectancy and cultural capital by linking them to discussions of technology. We argue for broadening the span of culturally important forms of capital by including the digital dimension of cultural capital. Based on data from the third-grade and fifth-grade waves of the Early Childhood Longitudinal…

Within the city-state of South Australia, the problem of attracting teachers to teach in rural schools is of long standing. We propose that "metrocentricity" can be viewed as a personal trait inhibiting teachers from considering country positions. In this project, 148 preservice teachers responded to an online survey concerning their…

The article considers a test of specification for quantile regressions. The test relies on the increase of the objective function and the worsening of the fit when unnecessary constraints are imposed. It compares the objective functions of restricted and unrestricted models and, in its different formulations, it verifies (a) forecast ability, (b)…

Hierarchical linear models (HLM) solve the problems associated with the unit of analysis problem such as misestimated standard errors, heterogeneity of regression and aggregation bias by modeling all levels of interest simultaneously. Hierarchical linear modeling resolves the problem of misestimated standard errors by incorporating a unique random…

Akaike's information criterion is suggested as a tool for evaluating fit and dimensionality in metric multidimensional scaling that uses least squares methods of estimation. This criterion combines the least squares loss function with the number of estimated parameters. Numerical examples are presented. The results from analyses of both simulation…

The sizable gender gap in college enrolment, especially among African Americans, constitutes a puzzling empirical regularity that may have serious consequences on marriage markets, male labor force participation and the diversity of college campuses. For instance, only 35.7 percent of all African American undergraduate students were men in 2004.…