Mokken scale analysis for polychotomous items: theory,a computer program and an empirical application

This paper contains three subjects. First, an extension of Mokken's nonparametric item response models from dichotomous items to items with two or more ordered answer categories is proposed. Second, a computer program to analyze multicategory item scores is presented. This program is called MSP. The analyses by means of MSP are based on the multicategory extension of Mokken's theory. Finally, an application of MSP to empirical multicategory test data is presented in order to illuminate its possibilities.     

Unfair dismissal legislation and property rights: some reflections

Starting from the premise that workers have ‘property rights’ in their jobs, this article considers ways in which British unfair dismissal legislation might be said to uphold such rights. The evidence indicates that remedies of compensation and re-employment afford minimal property rights to unfairly dismissed workers.     

Testing equality of variances in the analysis of repeated measurements

The problem of comparing the precisions of two instruments using repeated measurements can be cast as an extension of the Pitman-Morgan problem of testing equality of variances of a bivariate normal distribution. Hawkins (1981) decomposes the hypothesis of equal variances in this model into two subhypotheses for which simple tests exist. For the overall hypothesis he proposes to combine the tests of the subhypotheses using Fisher's method and empirically compares the component tests and their combination with the likelihood ratio test. In this paper an attempt is made to resolve some discrepancies and puzzling conclusions in Hawkins's study and to propose simple modifications.
The new tests are compared to the tests discussed by Hawkins and to each other both in terms of the finite sample power (estimated by Monte Carlo simulation) and theoretically in terms of asymptotic relative efficiencies.     

Government wage differentials

This paper shows that public sector wages usually exceed private but the size and composition of the differentials depend on sex and level of government. Using a technique derived from the literature on sex discrimination, these differentials are decomposed into a portion attributable to differences in productivity between the two types of workers and a portion ascribed to economic rent. This rent results from public workers' relatively greater political influence in the government wage-setting process and a systematic upward bias in public wages imparted by present government pay policy.     

Regression using mixed annual and quarterly data

By consideration of either Generalised Least-Squares of Theil-Goldberger estimates of equations for which data on the dependent variable is available for a subset of the sample period on only an annual basis, it is shown that best estimates of the equation coefficients may be obtained by Ordinary Least-Squares estimation over the complete set of quarterly observations with quarterly averages substituted for the missing quarterly data, and symmetrically for the corresponding observations on the regressor variables. The approach is extended to the Two-Stage Least-Squares case, and to the (structurally or stochastically) autoregressive case.     

MSE-improvement of the least squares estimator by dropping variables

It is well known that dropping variables in regression analysis decreases the variance of the least squares (LS) estimator of the remaining parameters. However, after elimination estimates of these parameters are biased, if the full model is correct. In his recent paper, Boscher (1991) showed that the LS-estimator in the special case of a mean shift model (cf. Cook and Weisberg, 1982) which assumes no “outliers” can be considered in the framework of a linear regression model where some variables are deleted. He derived conditions under which this estimator outperforms the LS-estimator of the full model in terms of the mean squared error (MSE)-matrix criterion. We demonstrate that this approach can be extended to the general set-up of dropping variables. Necessary and sufficient conditions for the MSE-matrix superiority of the LS-estimator in the reduced model over that in the full model are derived. We also provide a uniformly most powerful F-statistic for testing the MSE-improvement.