Misuse and Artifact in Factor Analytic Research

The theory of factor analysis has been developed for incorporating mathematical　statistical theories such as the maximum likelihood method and asymptotic methods. However, there have been several instances of misuse while employing procedures for factor analysis studies. In several studies, factor analysis has been performed by deleting items exhibiting the ceiling effect or floor effect. The number of samples required for factor analysis is not well known. Kaiser-Guttman criterion cannot be applied for determining the number of factors. Furthermore, various studies have employed Scree Graphs and Parallel Analysis for the said purpose, but no definitive method exists for the same. Orthogonal rotation methods such as Varimax cannot be considered as a conclusive solution. However, Geomin has been considered as a better rotation method not only for simple structure but also for more complex factor configuration. Simple structure and bifactor structure are discussed in connection to factor rotation problem. Although there are various artifacts associated with the usage of factor analysis, this issue can be addressed by verifying factorial invariance through multi-group simultaneous analysis incorporated by SEM programs such as Mplus and R Package.因子分析の理論は、最尤法と漸近的方法のような数理統計学的理論を組み込んだ形で発展してきた。しかしながら、因子分析研究の手順にはまだ誤用がみられる。いくつかの研究において、天井効果や床効果を示す項目を削除して因子分析が行われている。因子分析に必要なサンプル数は明確ではない。因子の数を決定するためにKaiser-Guttman 基準は使うことはできない。そして、この目的でScree Graph とParallel Analysis を使用している研究は数多くあるが、そのための決定的な方法はない。Varimax のような直交回転は最終的な解と考えることはできない。しかしながら、Geomin は単純構造だけでなくより複雑な因子の布置に対しても優れた回転方法と考えられている。因子回転問題を考慮した単純構造とbifactor 構造について議論した。因子分析の使い方には多くのartifacts があるが、この問題は、Mplus やR Package などのSEMプログラムによって組み込まれた複数集団の同時分析によって因子的不変性を検証することによって対処することができる

Reconstruction of metabolic networks from high-throughput metabolite profiling data: in silico analysis of red blood cell metabolism

We investigate the ability of algorithms developed for reverse engineering of transcriptional regulatory networks to reconstruct metabolic networks from high-throughput metabolite profiling data. For this, we generate synthetic metabolic profiles for benchmarking purposes based on a well-established model for red blood cell metabolism. A variety of data sets is generated, accounting for different properties of real metabolic networks, such as experimental noise, metabolite correlations, and temporal dynamics. These data sets are made available online. We apply ARACNE, a mainstream transcriptional networks reverse engineering algorithm, to these data sets and observe performance comparable to that obtained in the transcriptional domain, for which the algorithm was originally designed.Comment: 14 pages, 3 figures. Presented at the DIMACS Workshop on Dialogue on Reverse Engineering Assessment and Methods (DREAM), Sep 200

Comparing families of dynamic causal models

Mathematical models of scientific data can be formally compared using Bayesian model evidence. Previous applications in the biological sciences have mainly focussed on model selection in which one first selects the model with the highest evidence and then makes inferences based on the parameters of that model. This “best model” approach is very useful but can become brittle if there are a large number of models to compare, and if different subjects use different models. To overcome this shortcoming we propose the combination of two further approaches: (i) family level inference and (ii) Bayesian model averaging within families. Family level inference removes uncertainty about aspects of model structure other than the characteristic of interest. For example: What are the inputs to the system? Is processing serial or parallel? Is it linear or nonlinear? Is it mediated by a single, crucial connection? We apply Bayesian model averaging within families to provide inferences about parameters that are independent of further assumptions about model structure. We illustrate the methods using Dynamic Causal Models of brain imaging data

Optical-Depth Scaling of Light Scattering From a Dense and Cold Atomic \u3csup\u3e87\u3c/sup\u3eRb Gas

We report investigation of near-resonance light scattering from a cold and dense atomic gas of 87Rb atoms. Measurements are made for probe frequencies tuned near the F=2→ F\u27=3 nearly closed hyperfine transition, with particular attention paid to the dependence of the scattered light intensity on detuning from resonance, the number of atoms in the sample, and atomic sample size. We find that, over a wide range of experimental variables, the optical depth of the atomic sample serves as an effective single scaling parameter which describes well all the experimental data

Modelling Chinese grassland systems to improve herder livelihoods and grassland sustainability

Recent degradation of Chinese grasslands has contributed to declining herder productivity and profitability, increased incidence of dust storms and regionally reduced air quality. Overgrazing due to a doubling of stocking rates since the mid-1980s has been identified as a key contributing factor. Several pathways and strategies exist to improve grassland management; however, there remains uncertainty around the long-term sustainability of alternative systems. Nineteen years of grasslands research in China has produced a suite of models designed to improve understanding of grassland systems and investigate options for change. The StageTHREE Sustainable Grasslands Model was used to evaluate the ability of selected strategies to meet economic, production and environmental objectives. Sets of strategies that focussed on flock size, lambing and selling times, supplementary feeding rules and grazing management were simulated for a typical herder located in the desert steppe of Siziwang Banner, in the Inner Mongolia Autonomous Region of China. The results from the risk efficiency analysis indicated that no single strategy set clearly dominates across all objectives. Although the current practice of herders was found to be risk-efficient, it did not achieve the highest rate of grassland recovery, minimise soil erosion or minimise the greenhouse gas (GHG) emission intensity for sheepmeat production. Targeting further improvements in these attributes could be at the detriment of herder livelihoods. The analysis indicated that if herders adopted biomass-based grazing management and improved supplementary feeding they would be able to improve grassland resilience and maintain positive long-term economic performance under reduced flock sizes. Individual decision-making units, however, would still need to trade off the importance of different attributes to identify the strategy set, or system, that best meets their objectives and attitude to risk

HST Observations of Chromospheres in Metal Deficient Field Giants

HST high resolution spectra of metal-deficient field giants more than double the stars in previous studies, span about 3 magnitudes on the red giant branch, and sample an abundance range [Fe/H]= -1 to -3. These stars, in spite of their age and low metallicity, possess chromospheric fluxes of Mg II (2800 Angstrom) that are within a factor of 4 of Population I stars, and give signs of a dependence on the metal abundance at the lowest metallicities. The Mg II k-line widths depend on luminosity and correlate with metallicity. Line profile asymmetries reveal outflows that occur at lower luminosities (M_V = -0.8) than detected in Ca K and H-alpha lines in metal-poor giants, suggesting mass outflow occurs over a larger span of the red giant branch than previously thought, and confirming that the Mg II lines are good wind diagnostics. These results do not support a magnetically dominated chromosphere, but appear more consistent with some sort of hydrodynamic, or acoustic heating of the outer atmospheres.Comment: 36 pages, 12 figures, 7 tables, and accepted for publication in The Astronomical Journa