Generalised Rank Regression Estimator with Standard Error Adjusted Lasso

One of the standard variable selection procedures in multiple linear regression is to use a penalisation technique in least‐squares (LS) analysis. In this setting, many different types of penalties have been introduced to achieve variable selection. It is well known that LS analysis is sensitive to outliers, and consequently outliers can present serious problems for the classical variable selection procedures. Since rank‐based procedures have desirable robustness properties compared to LS procedures, we propose a rank‐based adaptive lasso‐type penalised regression estimator and a corresponding variable selection procedure for linear regression models. The proposed estimator and variable selection procedure are robust against outliers in both response and predictor space. Furthermore, since rank regression can yield unstable estimators in the presence of multicollinearity, in order to provide inference that is robust against multicollinearity, we adjust the penalty term in the adaptive lasso function by incorporating the standard errors of the rank estimator. The theoretical properties of the proposed procedures are established and their performances are investigated by means of simulations. Finally, the estimator and variable selection procedure are applied to the Plasma Beta‐Carotene Level data set.     

Estimation of Population Variance from Multi-ranker Ranked Set Sampling Designs

In this article, we develop an estimator for a population variance based on a multi-ranker ranked set sampling design. In a multi-ranker design, the units are ranked by more than one ranker allowing ties whenever the confidence level of the rankers is low. The ranking information of all rankers is then combined in a meaningful way to create a single measure. This measure is used to construct the sampling design and a new estimator for the population variance. The article investigates the bias and relative efficiency of the proposed variance estimator. It is shown that the new estimator performs as good as or better than its competitors in the literature.     

Inference in the presence of ranking error in ranked set sampling

The author proposes inference techniques for ranked set sample data in the presence of judgment ranking errors. He bases his analysis on the models of Bohn & Wolfe (1994) and Frey (2007a, b), of which parameters are estimated by minimizing a distance measure. He then uses the fitted models to calibrate confidence intervals and tests. He shows the validity of his approach through simulation and illustrates its application through the construction of distribution‐free confidence intervals for the median area of apple tree leaves covered by a spray.     

Linking Local Government Discretion and Accountability in Decentralisation

Decentralisation offers significant opportunities to improve government accountability by exerting stronger pressures both from below (demand) and above (supply). The literature contains many examples, however, where the potential has not been realised, partly because decentralisation reforms have often been introduced without thinking through their accountability implications. Even when accountability is taken into account, the efforts tend to emphasise either the supply or the demand side of the equation, but not both. Drawing on the sets of literature on fiscal, administrative and political decentralisation, this article presents a methodology for studying this.     

Nationalism and democracy in post‐communist Central Asia

The paper evaluates misconceptions of the so‐called transitologists in terms of the relationship between nationalism and democracy in the post‐Soviet Central Asian context. The analysis looks at only four of the five Central Asian republics: Kazakhstan, Kyrgyzstan, Turkmenistan and Uzbekistan. The paper puts forward two main arguments. First, contrary to the argument by some political scientists that nationalism is compatible with, and indeed is the same as, democracy, the author argues that there is a significant degree of trade‐off between nationalism and democracy. Second, contrary to the transitologists' assumptions that an incipient trend would enforce a regime change from communism to liberal democracy in all post‐communist cases, the author argues that it is indeed nationalism, not liberal democracy, that is the real successor to communism at least in Central Asian countries. The paper provides evidence indicating the pervasiveness of ethnic nationalism and the deficiencies of liberal democracy in post‐Soviet Central Asia.     

Functions of Concordance and Dependence with Related Measures

Some functions that serve as building blocks for construction of a wider range of modes of concordance and dependence are pointed. We probe into interplays of such modes. From the standpoint of their conformity to stochastic dominance ordering of distributions within a Fréchet class, all such derived modes display some parallelism under certain conditions. We finally suggest a novel numeric measure of dependence that covers similar existing measures in literature.     

Parametric inference based on judgment post stratified samples

In this paper, we consider a judgment post stratified (JPS) sample of set size $H$ from a location and scale family of distributions. In a JPS sample, ranks of measured units are random variables. By conditioning on these ranks, we derive the maximum likelihood (MLEs) and best linear unbiased estimators (BLUEs) of the location and scale parameters. Since ranks are random variables, by considering the conditional distributions of ranks given the measured observations we construct Rao-Blackwellized version of MLEs and BLUEs. We show that Rao-Blackwellized estimators always have smaller mean squared errors than MLEs and BLUEs in a JPS sample. In addition, the paper provides empirical evidence for the efficiency of the proposed estimators through a series of Monte Carlo simulations.     

Parental Speech and Gesture Input to Girls Versus Boys in Singletons and Twins

Journal of Nonverbal Behavior - Children show sex differences in early speech development, with girls producing a greater number and variety of words at an earlier age than boys (Berglund et al. in...     

The Coverage Probability of Confidence Intervals in One‐Way Analysis of Covariance after Two F Tests

Volume 3 of Analysis of Messy Data by Milliken & Johnson (2002) provides detailed recommendations about sequential model development for the analysis of covariance. In his review of this volume, Koehler (2002) asks whether users should be concerned about the effect of this sequential model development on the coverage probabilities of confidence intervals for comparing treatments. We present a general methodology for the examination of these coverage probabilities in the context of the two‐stage model selection procedure that uses two F tests and is proposed in Chapter 2 of Milliken & Johnson (2002). We apply this methodology to an illustrative example from this volume and show that these coverage probabilities are typically very far below nominal. Our conclusion is that users should be very concerned about the coverage probabilities of confidence intervals for comparing treatments constructed after this two‐stage model selection procedure.