Exercise-related menstrual dysfunction: implications for menopausal health

Physical activity is a well recognized approach to the enhancement of general health and wellbeing in both healthy and diseased populations. However, excessive activity can result in exercise-related menstrual dysfunction (ERMD), which can adversely affect bone health and increase the risk of infertility and cardiovascular events in later life. Physicians should maintain a high awareness of EMRD in assessing health risks in the menopausal woman.     

Remove unwanted variation retrieves unknown experimental designs

Remove unwanted variation (RUV) is an estimation and normalization system in which the underlying correlation structure of a multivariate dataset is estimated from negative control measurements, typically gene expression values, which are assumed to stay constant across experimental conditions. In this paper we derive the weight matrix which is estimated and incorporated into the generalized least squares estimates of RUV-inverse, and show that this weight matrix estimates the average covariance matrix across negative control measurements. RUV-inverse can thus be viewed as an estimation method adjusting for an unknown experimental design. We show that for a balanced incomplete block design (BIBD), RUV-inverse recovers intra- and interblock estimates of the relevant parameters and combines them as a weighted sum just like the best linear unbiased estimator (BLUE), except that the weights are globally estimated from the negative control measurements instead of being individually optimized to each measurement as in the classical, single measurement BIBD BLUE.     

Profile parallelism in repeated measures designs

Three statistics are developed to test tor treatment by time interaction after a certain point in repeated measures designs under several covariance matrix configurations, viz., unstructured, spherically symmetric and autoregressive. An example is fully developed.     

Experiencing and writing Indigeneity, rurality and gender: Australian reflections

This paper has two interrelated aims. The first is to contribute to knowledge about rurality, gender and Indigeneity. This is undertaken by the first author, Bebe Ramzan, an Indigenous woman living in the Anangu Pitjantjatjara Yankunytjatjara (APY) Lands. Bebe shows similarities across rural and remote areas in Australia and details her knowledge and experience of home, rurality, rural communities, land and gender. The second aim of the paper is to examine issues surrounding the involvement of academic white women in Indigenous research. Writing from the position of feminist white women Barbara Pini and Lia Bryant reflect on theories of whiteness as cultural practice and in this paper contest representations of rurality in rural studies as white.     

Individuals in Context and Contexts in Individuals

This presentation will explore some ideas about the impact of both external and internal contexts on what we, whether as clients or therapists, do. It will offer a way of thinking about the internal and external as sides of the same coin, and a justification for working directly with one or the other whilst holding both in mind. In reflecting on how the internal and external affect therapists, attention will be given to both the hidden influence of personal experience in our ideas and the influence of radical doubt.     

Incorporating Previous Results Into the Analysis of General Balanced Designed Experiments

When previous results are available about quantities of interest in a designed experiment they should be incorporated into the analysis. We suppose that estimates of treatment effects and variance components and their precisions are available from previous data but not necessarily the full data. A prior-posterior method is described which incorporates these previous estimates directly into the analysis of a current set of data. General but concise formula are derived for the class of generally balanced designs. Previous results are represented by a multivariate normal prior for the treatment means and independent inverse chi-squared distributions for the variance components. Joint and marginal posterior modes and a measure of dispersion are proposed as combined or updated estimates. These posterior summary statistics have highly interpretable forms and are readily computed.     

THE ANALYSIS OF MULTISTRATA DESIGNED EXPERIMENTS WITH INCOMPLETE DATA

Building upon early work of E. A. Cornish we show that G. N. Wilkinson's version of Yates' approach to the analysis of designed experiments with a single error stratum carries over completely to designs with an arbitrary non-singular covariance matrix, initially assumed known. We show that the equations, corrections, adjustments and algorithms all have their more general analogues and that these can be solved, computed or executed quite readily if the design has orthogonal block structure and satisfies Nelder's condition of general balance. The results are illustrated with a split-plot and a simple (square) lattice design.     

A model selection approach for the identification of quantitative trait loci in experimental crosses

Summary. We consider the problem of identifying the genetic loci (called quantitative trait loci (QTLs)) contributing to variation in a quantitative trait, with data on an experimental cross. A large number of different statistical approaches to this problem have been described; most make use of multiple tests of hypotheses, and many consider models allowing only a single QTL. We feel that the problem is best viewed as one of model selection. We discuss the use of model selection ideas to identify QTLs in experimental crosses. We focus on a back-cross experiment, with strictly additive QTLs, and concentrate on identifying QTLs, considering the estimation of their effects and precise locations of secondary importance. We present the results of a simulation study to compare the performances of the more prominent methods.     

ON A SHARED ALLELE TEST OF RANDOM MATING

A simple random sample is observed from a population with a large number‘K’ of alleles, to test for random mating. Of n couples, n_ijkl have female genotype ij and male genotype kl (i, j, k, l{1,…, A‘}). The large contingency table is collapsed into three counts, n₀, n₁ and n₂ where n_p is the number of couples with s alleles in common (s = 0,1, 2). The counts are estimated by np?_o where n₀, is the estimated probability of a couple having s alleles in common under the hypothesis of random mating. The usual chi-square goodness of fit statistic X² compares observed (n_s) with expected (np?) over the three categories, s = 0,1,2. An empirical observation has suggested that X² is close to having a chi-square distribution with two degrees of freedom (X) despite a large number of parameters implicitly estimated in _e. This paper gives two theorems which show that x is indeed the approximate distribution of X² for large n and K₁“, provided that no allele type over-dominates the others.