POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models

The POWERLIB SAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the "univariate" approach to repeated measures (UNIREP), the Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda tests in "multivariate" approach (MULTIREP), as well as a limited but useful range of mixed models. The familiar univariate linear model with Gaussian errors is an important special case. For estimated covariance, the software provides confidence limits for the resulting estimated power. All power and confidence limits values can be output to a SAS dataset, which can be used to easily produce plots and tables for manuscripts.

Geometry unites synchrony, chimeras, and waves in nonlinear oscillator networks

One of the simplest mathematical models in the study of nonlinear systems is the Kuramoto model, which describes synchronization in systems from swarms of insects to superconductors. We have recently found a connection between the original, real-valued nonlinear Kuramoto model and a corresponding complex-valued system that permits describing the system in terms of a linear operator and iterative update rule. We now use this description to investigate three major synchronization phenomena in Kuramoto networks (phase synchronization, chimera states, and traveling waves), not only in terms of steady state solutions but also in terms of transient dynamics and individual simulations. These results provide new mathematical insight into how sophisticated behaviors arise from connection patterns in nonlinear networked systems

Geometry unites synchrony, chimeras, and waves in nonlinear oscillator networks

One of the simplest mathematical models in the study of nonlinear systems is the Kuramoto model, which describes synchronization in systems from swarms of insects to superconductors. We have recently found a connection between the original, real-valued nonlinear Kuramoto model and a corresponding complex-valued system that permits describing the system in terms of a linear operator and iterative update rule. We now use this description to investigate three major synchronization phenomena in Kuramoto networks (phase synchronization, chimera states, and traveling waves), not only in terms of steady state solutions but also in terms of transient dynamics and individual simulations. These results provide new mathematical insight into how sophisticated behaviors arise from connection patterns in nonlinear networked systems

POWERLIB: SAS/IML Software for Computing Power in Multivariate Linear Models

The POWERLIB SAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the "univariate" approach to repeated measures (UNIREP), the Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda tests in "multivariate" approach (MULTIREP), as well as a limited but useful range of mixed models. The familiar univariate linear model with Gaussian errors is an important special case. For estimated covariance, the software provides confidence limits for the resulting estimated power. All power and confidence limits values can be output to a SAS dataset, which can be used to easily produce plots and tables for manuscripts

Australian-Antarctic breakup and seafloor spreading: Balancing geological and geophysical constraints

The motion of diverging tectonic plates is typically constrained by geophysical data from preserved ocean crust. However, constraining plate motions during continental rifting and the breakup process relies on balancing evidence from a diverse range of geological and geophysical observations, often subject to differing interpretations. Reconstructing the evolution of rifting and breakup between Australia and Antarctica epitomizes the challenges involved in creating detailed models of Pangea breakup. In this example, differing degrees of emphasis on and alternative interpretations of offshore geophysical data, in particular magnetic anomalies and seismic reflection profiles, and onshore geological data, lead to starkly contrasting views of how the continents were configured at the onset of Mesozoic rifting. Here, we critically review reconstructions of rifting and breakup in the light of all available geological and geophysical data, including magnetic anomalies, fracture zones, conjugate crustal domains, amounts of continental extension, continental geology, plate boundary locations, break-up ages and stratigraphy. We identify the most viable plate tectonic reconstructions both with and without the input of the oldest, more controversial magnetic anomaly interpretations, and discuss implications for reconstructions of other margin pairs. Our analysis highlights key discrepancies between reconstructions based solely on geological piercing points, and those based on a range of constraints. These insights provide a powerful framework for reducing the range of viable models for Australian-Antarctic rifting, and provide key lessons for future efforts aimed at constraining pre- and syn-rift plate tectonic reconstructions. © 2018 Elsevier B.V.S.E.W. and R.D.M. were supported by ARC grants DP130101946 and IH130200012 . J.M.W. was supported by ARC grant DE140100376 . J.A.H was supported under Australian Research Council ‘s Special Research Initiative for Antarctic Gateway Partnership SR140300001 . S.E.W. and J.M.W. were supported by ARC grant DP180102280

Power calculation for overall hypothesis testing with high-dimensional commensurate outcomes: Overall power for HDLSS

The complexity of system biology means that any metabolic, genetic, or proteomic pathway typically includes so many components (e.g., molecules) that statistical methods specialized for overall testing of high-dimensional and commensurate outcomes are required. While many overall tests have been proposed, very few have power and sample size methods. We develop accurate power and sample size methods and software to facilitate study planning for high-dimensional pathway analysis. With an account of any complex correlation structure between high-dimensional outcomes, the new methods allow power calculation even when the sample size is less than the number of variables. We derive the exact (finite-sample) and approximate non-null distributions of the ‘univariate’ approach to repeated measures test statistic, as well as power-equivalent scenarios useful to generalize our numerical evaluations. Extensive simulations of group comparisons support the accuracy of the approximations even when the ratio of number of variables to sample size is large. We derive a minimum set of constants and parameters sufficient and practical for power calculation. Using the new methods and specifying the minimum set to determine power for a study of metabolic consequences of vitamin B6 deficiency helps illustrate the practical value of the new results. Free software implementing the power and sample size methods applies to a wide range of designs, including one group pre-intervention and post-intervention comparisons, multiple parallel group comparisons with one-way or factorial designs, and the adjustment and evaluation of covariate effects

POWERLIB : SAS/IML Software for Computing Power in Multivariate Linear Models

The POWERLIB SAS/IML software provides convenient power calculations for a wide range of multivariate linear models with Gaussian errors. The software includes the Box, Geisser-Greenhouse, Huynh-Feldt, and uncorrected tests in the “univariate” approach to repeated measures (UNIREP), the Hotelling Lawley Trace, Pillai-Bartlett Trace, and Wilks Lambda tests in “multivariate” approach (MULTIREP), as well as a limited but useful range of mixed models. The familiar univariate linear model with Gaussian errors is an important special case. For estimated covariance, the software provides confidence limits for the resulting estimated power. All power and confidence limits values can be output to a SAS dataset, which can be used to easily produce plots and tables for manuscripts

Morphological features in a Xhosa schizophrenia population

BACKGROUND: Demonstrating an association between physical malformation and schizophrenia could be considered supportive of a neurodevelopmental origin of schizophrenia and may offer insights into a critical period for the development of this illness. The aim of our study was to investigate whether differences in the presence of minor physical anomalies could be demonstrated between schizophrenia sufferers and normal controls in a Xhosa population with a view to identifying a means of subtyping schizophrenia for use in future genetic studies. METHODS: Sixty-three subjects with schizophrenia (21 sibling pairs, 1 sibship of four and a group of probands with an affected non-participating sibling (n = 17)), 81 normal controls (37 singletons and 22 sibling pairs) of Xhosa ethnicity were recruited. Each participant was then examined for minor physical anomalies using the Modified Waldrop scale. The relationship between each of the morphological features and the presence of an affected sib was examined using the Chi-squared test, followed by an intra-pair concordance analysis in the sibling pairs. RESULTS: Gap between first and second toes was significantly more common in the affected sib pair group when compared to the non-affected sib pair group (p = 0.019) and non-affected singleton control group (p = 0.013). Concordance analysis also revealed increased concordance for this item in the affected sib pair group. CONCLUSION: These findings offer an intriguing possibility that in the Xhosa population, affected sib pair status may be linked to a neurodevelopmental insult during a specific period of the fetal developmental

Detection and follow-up of chronic obstructive pulmonary disease (COPD) and risk factors in the Southern Cone of Latin America. the pulmonary risk in South America (PRISA) study

<p>Abstract</p> <p>Background</p> <p>The World Health Organization has estimated that by 2030, chronic obstructive pulmonary disease will be the third leading cause of death worldwide. Most knowledge of chronic obstructive pulmonary disease is based on studies performed in Europe or North America and little is known about the prevalence, patient characteristics and change in lung function over time in patients in developing countries, such as those of Latin America. This lack of knowledge is in sharp contrast to the high levels of tobacco consumption and exposure to biomass fuels exhibited in Latin America, both major risk factors for the development of chronic obstructive pulmonary disease. Studies have also demonstrated that most Latin American physicians frequently do not follow international chronic obstructive pulmonary disease diagnostic and treatment guidelines. The PRISA Study will expand the current knowledge regarding chronic obstructive pulmonary disease and risk factors in Argentina, Chile and Uruguay to inform policy makers and health professionals on the best policies and practices to address this condition.</p> <p>Methods/Design</p> <p>PRISA is an observational, prospective cohort study with at least four years of follow-up. In the first year, PRISA has employed a randomized three-staged stratified cluster sampling strategy to identify 6,000 subjects from Marcos Paz and Bariloche, Argentina, Temuco, Chile, and Canelones, Uruguay. Information, such as comorbidities, socioeconomic status and tobacco and biomass exposure, will be collected and spirometry, anthropometric measurements, blood sampling and electrocardiogram will be performed. In year four, subjects will have repeat measurements taken.</p> <p>Discussion</p> <p>There is no longitudinal data on chronic obstructive pulmonary disease incidence and risk factors in the southern cone of Latin America, therefore this population-based prospective cohort study will fill knowledge gaps in the prevalence and incidence of chronic obstructive pulmonary disease, patient characteristics and changes in lung function over time as well as quality of life and health care resource utilization. Information gathered during the PRISA Study will inform public health interventions and prevention practices to reduce risk of COPD in the region.</p