Robert L. Paige

Group and home-based tai chi in elderly subjects with knee osteoarthritis: a randomized controlled trial

Objective: To evaluate the effects of tai chi consisting of group and home-based sessions in elderly subjects with knee osteoarthritis. Design: A randomized, controlled, single-blinded 12-week trial with stratification by age and sex, and six weeks of follow-up. Setting: General community. Participants: Forty-one adults (709 / 9.2 years) with knee osteoarthritis. Interventions: The tai chi programme featured six weeks of group tai chi sessions, 40 min/session, three times a week, followed by another six weeks (weeks 7 -12) of home-based tai chi training. Subjects were requested to discontinue tai chi training during a six-week follow-up detraining period (weeks 13-18). Subjects in the attention control group attended six weeks of health lectures following the same schedule as the group-based tai chi intervention (weeks 0 -6), followed by 12 weeks of no activity (weeks 7-18). Main outcome measures: Knee pain measured by visual analogue scale, knee range of motion and physical function measured by Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC) were recorded at baseline and every three weeks throughout the 18-week study period. Data were analysed using a mixed model ANOVA. Results: The six weeks of group tai chi followed by another six weeks of home tai chi training showed significant improvements in mean overall knee pain (P = 0.0078), maximum knee pain (P = 0.0035) and the WOMAC subscales of physical function (P = 0.0075) and stiffness (P = 0.0206) compared to the baseline. No significant change of any outcome measure was noted in the attention control group throughout the study. The tai chi group reported lower overall pain and better WOMAC physical function than the attention control group at weeks 9 and 12. All improvements disappeared after detraining.

Comparison of the Effects of Tai Chi and Resistance Training on Bone Metabolism in the Elderly: A Feasibility Study

This feasibility study compared the effects of Tai Chi (TC) and resistance training (RT) on bone metabolism in the elderly. Twenty eight sedentary, elder adults, were randomized into either TC (n = 14, 78.8 +/-1.3 years) or RT (n = 14, 79.4 +/-2.2 years) to participate in 40 min of exercise per session, 3 sessions/week for 24 weeks. The outcome measures assessed were the concentrations of serum bone-specific alkaline phosphatase (BAP), pyridinoline (PYD), parathyroid hormone (PTH) and calcium, and urinary calcium. The TC group had a higher compliance rate than the RT group. After 6 weeks, (i) both TC and RT resulted in higher level of serum BAP relative to the baseline and the TC group exhibited a greater increase in serum BAP than the RT group; (ii) there was an increase of serum PYD in the RT group only, not in the TC group; and (iii) the BAP/PYD ratio was higher than baseline only in the TC group, and the increase of the ratio in the TC group was greater than that in the RT group. After 12 weeks, the increase in serum PTH in the TC group was higher than the RT group. After 24 weeks, there was a reduction of the urinary calcium level in the TC group relative to the baseline. In conclusion, these findings support that TC is beneficial for increasing bone formation in elderly, and long-term application is needed to substantiate the effect of TC as an alternative exercise in promotion of bone health.

Microhabitat characteristics of Akodon montensis, a reservoir for hantavirus, and hantaviral seroprevalence in an Atlantic forest site in eastern Paraguay

ABSTRACT: Hantaviruses may cause serious disease when transmitted to humans by their rodent hosts. Since their emergence in the Americas in 1993, there have been extensive efforts to understand the role of environmental factors on the presence of these viruses in their host rodent populations. HPS outbreaks have been linked to precipitation, but climatic factors alone have not been sufficient to predict the spatial-temporal dynamics of the environment-reservoir-virus system. Using a series of mark-recapture sampling sites located at the Mbaracayú Biosphere Reserve, an Atlantic Forest site in eastern Paraguay, we investigated the hypothesis that microhabitat might also influence the prevalence of Jaborá hantavirus within populations of its reservoir species, Akodon montensis. Seven trapping sessions were conducted during 2005–2006 at four sites chosen to capture variable microhabitat conditions within the study site. Analysis of microhabitat preferences showed that A. montensis preferred areas with little forest overstory and denser vegetation cover on and near the ground. Moreover, there was a significant difference in the microhabitat occupied by antibody-positive vs antibody-negative rodents, indicating that microhabitats with greater overstory cover may promote transmission and maintenance of hantavirus in A. montensis.

The Hodrick-prescott Filter: A Special Case of Penalized Spline Smoothing

We prove that the Hodrick-Prescott Filter (HPF), a commonly used method for smoothing econometric time series, is a special case of a linear penalized spline model with knots placed at all observed time points (except the first and last) and uncorrelated residuals. This equivalence then furnishes a rich variety of existing data-driven parameter estimation meth- ods, particularly restricted maximum likelihood (REML) and generalized cross-validation (GCV). This has profound implications for users of HPF who have hitherto typically relied on subjective choice, rather than estima- tion, for the smoothing parameter. By viewing estimates as roots of an ap- propriate quadratic estimating equation, we also present a new approach for constructing confidence intervals for the smoothing parameter. The method is akin to a parametric bootstrap where Monte Carlo simulation is replaced by saddlepoint approximation, and provides a fast and accurate alternative to exact methods, when they exist, e.g. REML. More importantly, it is also the only computationally feasible method when no other methods, exact or otherwise, exist, e.g. GCV. The methodology is demonstrated on the Gross National Product (GNP) series originally analyzed by Hodrick and Prescott (1997). With proper attention paid to residual correlation struc- ture, we show that REML-based estimation delivers an appropriate smooth for both the GNP series and its returns.

A habitat-based model for the spread of hantavirus between reservoir and spillover species

Abstract New habitat-based models for spread of hantavirus are developed which account for interspecies interaction. Existing habitat-based models do not consider interspecies pathogen transmission, a primary route for emergence of new infectious diseases and reservoirs in wildlife and man. The modeling of interspecies transmission has the potential to provide more accurate predictions of disease persistence and emergence dynamics. The new models are motivated by our recent work on hantavirus in rodent communities in Paraguay. Our Paraguayan data illustrate the spatial and temporal overlaps among rodent species, one of which is the reservoir species for Jabora virus and others which are spillover species. Disease transmission occurs when their habitats overlap. Two mathematical models, a system of ordinary differential equations (ODE) and a continuous-time Markov chain (CTMC) model, are developed for spread of hantavirus between a reservoir and a spillover species. Analysis of a special case of the ODE model provides an explicit expression for the basic reproduction number, R 0 , such that if R 0 < 1 , then the pathogen does not persist in either population but if R 0 > 1 , pathogen outbreaks or persistence may occur. Numerical simulations of the CTMC model display sporadic disease incidence, a new behavior of our habitat-based model, not present in other models, but which is a prominent feature of the seroprevalence data from Paraguay. Environmental changes that result in greater habitat overlap result in more encounters among various species that may lead to pathogen outbreaks and pathogen establishment in a new host.

Aligned Rank Transform Techniques for Analysis of Variance and Multiple Comparisons

Abstract The aligned rank transform (ART) technique for testing linear hypotheses and performing multiple comparisons is known to provide a powerful and robust nonparametric alternative to the usual classical analysis techniques where a normal error distribution is assumed. ART procedures are also known to provide results that are more powerful and robust when compared with other procedures. In this paper, we review the ART testing procedures in linear models. We pay special attention to the two-way layout and multiple comparison techniques, and attempt to show the ease with which the ART methods can be implemented by researchers desiring a nonparametric alternative to the usual least squares methods. Some examples are given for analyzing a two-way layout and performing multiple comparisons. The results of a small-scale simulation study are also presented to show that the ART testing procedures may be quite robust against violations of the assumption of a continuous error distribution.

Exact distributional computations for Roy's statistic and the largest eigenvalue of a Wishart distribution

Computational expressions for the exact CDF of Roy’s test statistic in MANOVA and the largest eigenvalue of a Wishart matrix are derived based upon their Pfaffian representations given in Gupta and Richards (SIAM J. Math. Anal. 16:852–858, 1985). These expressions allow computations to proceed until a prespecified degree of accuracy is achieved. For both distributions, convergence acceleration methods are used to compute CDF values which achieve reasonably fast run times for dimensions up to 50 and error degrees of freedom as large as 100. Software that implements these computations is described and has been made available on the Web.

On testing common indices for two multi-index models

We propose a link-free procedure for testing whether two multi-index models share identical indices via the sufficient dimension reduction approach. Test statistics are developed based upon three different sufficient dimension reduction methods: (i) sliced inverse regression, (ii) sliced average variance estimation and (iii) directional regression. The asymptotic null distributions of our test statistics are derived. Monte Carlo studies are performed to investigate the efficacy of our proposed methods. A real-world application is also considered.

Small Sample LD50 Confidence Intervals Using Saddlepoint Approximations

Confidence intervals for the median lethal dose (LD50) and other dose percentiles in logistic regression models are developed using a generalization of the Fieller theorem for exponential families and saddlepoint approximations. Simulation results show that, in terms of one-tailed and two-tailed coverage, the proposed methodology generally outperforms competing confidence intervals obtained from the classical Fieller, likelihood ratio, and score methods. In terms of two-tailed coverage, the proposed method is comparable to the Bartlett-corrected likelihood ratio method, but generally outperforms it in terms of one-tailed coverage. An extension to the competing risk setting is presented that allows binary response adjustments to be made using observed censoring times. Supplementary materials for this article are available online at http://pubs.amstat.org.

Challenges in Topological Object Data Analysis

Statistical analysis on object data presents many challenges. Basic summaries such as means and variances are difficult to compute. We apply ideas from topology to study object data. We present a framework for using death vectors and persistence landscapes to vectorize object data and perform statistical analysis. We apply this method to some common leaf images that were previously shown to be challenging to compare using a 3D shape techniques. Surprisingly, the most persistent features are shown to be “topological noise” and the statistical analysis depends on the less persistent features which we refer to as the “geometric signal”. We also describe the first steps to a new approach to using topology for object data analysis, which applies topology to distributions on object spaces. We introduce a new Frechet-Morse function technique for probability distribution on a compact object space, extending the Frechet means lo a larger number of location parameters, including Frechet antimeans. An example of 3D data analysis to distinguish two flowers using the new location parameters associated with a Veronese-Whitney (VW) embedding of random projective shapes of 3D configurations extracted from a set of pairs of their digital camera images is also given here.Statistical analysis on object data presents many challenges. Basic summaries such as means and variances are difficult to compute. We apply ideas from topology to study object data. We present a framework for using persistence landscapes to vectorize object data and perform statistical analysis. We apply to this pipeline to some biological images that were previously shown to be challenging to study using shape theory. Surprisingly, the most persistent features are shown to be “topological noise” and the statistical analysis depends on the less persistent features which we refer to as the “geometric signal”. We also describe the first steps to a new approach to using topology for object data analysis, which applies topology to distributions on object spaces.