Estimating Income Inequality in China Using Grouped Data and the Generalized Beta Distribution

There are two main types of data sources of income distributions in China: household survey data and grouped data. Household survey data are typically available for isolated years and individual provinces. In comparison, aggregate or grouped data are typically available more frequently and usually have national coverage. In principle, grouped data allow investigation of the change of inequality over longer, continuous periods of time, and the identification of patterns of inequality across broader regions. Nevertheless, a major limitation of grouped data is that only mean (average) income and income shares of quintile or decile groups of the population are reported. Directly using grouped data reported in this format is equivalent to assuming that all individuals in a quintile or decile group have the same income. This potentially distorts the estimate of inequality within each region. The aim of this paper is to apply an improved econometric method designed to use grouped data to study income inequality in China. A generalized beta distribution is employed to model income inequality in China at various levels and periods of time. The generalized beta distribution is more general and flexible than the lognormal distribution that has been used in past research, and also relaxes the assumption of a uniform distribution of income within quintile and decile groups of populations. The paper studies the nature and extent of inequality in rural and urban China over the period 1978 to 2002. Income inequality in the whole of China is then modeled using a mixture of province-specific distributions. The estimated results are used to study the trends in national inequality, and to discuss the empirical findings in the light of economic reforms, regional policies, and globalization of the Chinese economy.

Do generalized visual training programmes for sport really work? An experimental investigation

We assessed the effectiveness of two generalized visual training programmes in enhancing visual and motor performance for racquet sports. Forty young participants were assigned equally to groups undertaking visual training using Revien and Gabor's Sports Vision programme (Group 1), visual training using Revien's Eyerobics (Group 2), a placebo condition involving reading (Group 3) and a control condition involving physical practice only (Group 4). Measures of basic visual function and of sport-specific motor performance were obtained from all participants before and immediately after a 4-week training period. Significant pre- to post-training differences were evident on some of the measures; however, these were not group-dependent. Contrary to the claims made by proponents of generalized visual training, we found no evidence that the visual training programmes led to improvements in either vision or motor performance above and beyond those resulting simply from test familiarity.

Fitting genetic models to twin data with binary and ordered categorical responses: A comparison of structural equation modelling and Bayesian hierarchical models

We compare Bayesian methodology utilizing free-ware BUGS (Bayesian Inference Using Gibbs Sampling) with the traditional structural equation modelling approach based on another free-ware package, Mx. Dichotomous and ordinal (three category) twin data were simulated according to different additive genetic and common environment models for phenotypic variation. Practical issues are discussed in using Gibbs sampling as implemented by BUGS to fit subject-specific Bayesian generalized linear models, where the components of variation may be estimated directly. The simulation study (based on 2000 twin pairs) indicated that there is a consistent advantage in using the Bayesian method to detect a correct model under certain specifications of additive genetics and common environmental effects. For binary data, both methods had difficulty in detecting the correct model when the additive genetic effect was low (between 10 and 20%) or of moderate range (between 20 and 40%). Furthermore, neither method could adequately detect a correct model that included a modest common environmental effect (20%) even when the additive genetic effect was large (50%). Power was significantly improved with ordinal data for most scenarios, except for the case of low heritability under a true ACE model. We illustrate and compare both methods using data from 1239 twin pairs over the age of 50 years, who were registered with the Australian National Health and Medical Research Council Twin Registry (ATR) and presented symptoms associated with osteoarthritis occurring in joints of the hand.

Efficacy of sertraline in a 12-week trial for generalized anxiety disorder

Objective: Sertraline's efficacy and tolerability in treating generalized anxiety disorder were evaluated. Method: Adult outpatients with DSM-IV generalized anxiety disorder and a total score of 18 or higher on the Hamilton Anxiety Rating Scale were eligible. After a 1-week single-blind placebo lead-in, patients were randomly assigned to 12 weeks of double-blind treatment with placebo (N=188, mean baseline anxiety score=25) or flexible doses (50-150 mg/day) of sertraline (N=182, mean anxiety score=25). The primary outcome measure was baseline-to-endpoint change in the Hamilton anxiety scale total score. A secondary efficacy measure was the Clinical Global Impression (CGI) improvement score; response was defined as a score of 2 or less. Results: Sertraline patients had significantly greater improvement than placebo patients on all efficacy measures at week 4. Analysis of covariance of the intent-to-treat group at endpoint (with the last observation carried forward) showed a significant difference in the decrease from baseline of the least-square mean total score on the Hamilton anxiety scale between sertraline (mean=11.7) and placebo (mean=8.0). Significantly greater endpoint improvement with sertraline than placebo was obtained for mean scores on the Hamilton anxiety scale psychic factor (6.7 versus 4.1) and somatic factor (5.0 versus 3.9). The rate of responders, based on CGI improvement and last observation carried forward, was significantly higher for sertraline (63%) than placebo (37%). Sertraline was well tolerated; 8% of patients versus 10% for placebo dropped out because of adverse events. Conclusions: Sertraline appears to be efficacious and well tolerated in the treatment of generalized anxiety disorder.

Single patient (n-of-1) trials with binary treatment preference

The use of a fully parametric Bayesian method for analysing single patient trials based on the notion of treatment 'preference' is described. This Bayesian hierarchical modelling approach allows for full parameter uncertainty, use of prior information and the modelling of individual and patient sub-group structures. It provides updated probabilistic results for individual patients, and groups of patients with the same medical condition, as they are sequentially enrolled into individualized trials using the same medication alternatives. Two clinically interpretable criteria for determining a patient's response are detailed and illustrated using data from a previously published paper under two different prior information scenarios. Copyright (C) 2005 John Wiley & Sons, Ltd.

Designs for generalized linear models with several variables and model uncertainty

Standard factorial designs sometimes may be inadequate for experiments that aim to estimate a generalized linear model, for example, for describing a binary response in terms of several variables. A method is proposed for finding exact designs for such experiments that uses a criterion allowing for uncertainty in the link function, the linear predictor, or the model parameters, together with a design search. Designs are assessed and compared by simulation of the distribution of efficiencies relative to locally optimal designs over a space of possible models. Exact designs are investigated for two applications, and their advantages over factorial and central composite designs are demonstrated.

Orbital currents and charge density waves in a generalized Hubbard ladder

We study a generalized Hubbard model on the two-leg ladder at zero temperature, focusing on a parameter region with staggered flux (SF)/d-density wave (DDW) order. To guide our numerical calculations, we first investigate the location of a SF/DDW phase in the phase diagram of the half-filled weakly interacting ladder using a perturbative renormalization group (RG) and bosonization approach. For hole doping 6 away from half-filling, finite-system density-matrix renormalizationgroup (DMRG) calculations are used to study ladders with up to 200 rungs for intermediate-strength interactions. In the doped SF/DDW phase, the staggered rung current and the rung electron density both show periodic spatial oscillations, with characteristic wavelengths 2/delta and 1/delta, respectively, corresponding to ordering wavevectors 2k(F) and 4k(F) for the currents and densities, where 2k(F) = pi(1 - delta). The density minima are located at the anti-phase domain walls of the staggered current. For sufficiently large dopings, SF/DDW order is suppressed. The rung density modulation also exists in neighboring phases where currents decay exponentially. We show that most of the DMRG results can be qualitatively understood from weak-coupling RG/bosonization arguments. However, while these arguments seem to suggest a crossover from non-decaying correlations to power-law decay at a length scale of order 1/delta, the DMRG results are consistent with a true long-range order scenario for the currents and densities. (c) 2005 Elsevier Inc. All rights reserved.

Australian Newspaper History Group Newsletter

Current findings related to the history of Australian newspapers.

Australian Newspaper History Group Newsletter

Current findings, news and announcements related to the history of Australian newspapers.

Australian Newspaper History Group Newsletter

Current findings, news and announcements related to the history of Australian newspapers.

Group outside the Sub Inspector Office during Ky visit

Group of people outside the Sub Inspector Office during visit of former South Vietnamese vice president Nguyen Cao Ky to Brisbane, Australia in January 1967.

Group of marchers during Mayday procession 1966 Brisbane, Australia

Group of marchers during Mayday procession 1966 Brisbane, Australia including children and dog. The group is passing Pearl Assurance House in Queen Street, Brisbane. Marchers have flags and banners relating to anti war and anti nuclear tests.

Sampling phylogenetic tree space with the generalized Gibbs sampler

The generalized Gibbs sampler (GGS) is a recently developed Markov chain Monte Carlo (MCMC) technique that enables Gibbs-like sampling of state spaces that lack a convenient representation in terms of a fixed coordinate system. This paper describes a new sampler, called the tree sampler, which uses the GGS to sample from a state space consisting of phylogenetic trees. The tree sampler is useful for a wide range of phylogenetic applications, including Bayesian, maximum likelihood, and maximum parsimony methods. A fast new algorithm to search for a maximum parsimony phylogeny is presented, using the tree sampler in the context of simulated annealing. The mathematics underlying the algorithm is explained and its time complexity is analyzed. The method is tested on two large data sets consisting of 123 sequences and 500 sequences, respectively. The new algorithm is shown to compare very favorably in terms of speed and accuracy to the program DNAPARS from the PHYLIP package.