Measuring college sailing teams ability: an application of the many-facet Rasch model to ordinal data

For those who look at typical approaches to sports ranking, sailing seems an almost impossible challenge, thereby making the evidence supporting Rasch measurement in this study even more intriguing. This article describes our application of MFRM and the results from our analysis of one year's data from the North American college sailing competitions. We discuss the following issues for inclusion in the development of a Rasch model useful to college sailing team ability: 1. The level of data quality (as described by Stevens, 1946) 2. The connectedness of the contests 3. Empty cells (missing data) 4. Interpreting outliers, trends, or unusual results 5. Judges' or polls' bias Our results indicate the utility and precision of MFRM as a tool generally appropriate for ordinal ranking applications and sailing ability specifically.     

A multidimensional generalized many-facet Rasch model for rubric-based performance assessment

Behaviormetrika - Performance assessment, in which human raters assess examinee performance in a practical task, often involves the use of a scoring rubric consisting of multiple evaluation items...     

Error measures for resampled irregular data

With resampling, a regularly sampled signal is extracted from observations which are irregularly spaced in time. Resampling methods can be divided into simple and complex methods. Simple methods such as Sample and Hold (S and H) and Nearest Neighbor Resampling (NNR) use only one irregular sample for one resampled observation. A theoretical analysis of the simple methods is given. The various resampling methods are compared using the new error measure SD_T: the spectral distortion at interval T. SD_T is zero when the time domain properties of the signal are conserved. Using the time domain approach, an antialiasing filter is no longer necessary: the best possible estimates are obtained by using the data themselves. In the frequency domain approach, both allowing aliasing and applying antialiasing leads to distortions in the spectrum. The error measure SD_T has been compared to the reconstruction error. A small reconstruction error does not necessarily result in an accurate estimate of the statistical signal properties as expressed by SD_T     

Detecting and measuring rater effects using many-facet Rasch measurement: part I

The purpose of this two-part paper is to introduce researchers to the many-facet Rasch measurement (MFRM) approach for detecting and measuring rater effects. The researcher will learn how to use the Facets (Linacre, 2001) computer program to study five effects: leniency/severity, central tendency, randomness, halo, and differential leniency/severity. Part 1 of the paper provides critical background and context for studying MFRM. We present a catalog of rater effects, introducing effects that researchers have studied over the last three-quarters of a century in order to help readers gain a historical perspective on how those effects have been conceptualized. We define each effect and describe various ways the effect has been portrayed in the research literature. We then explain how researchers theorize that the effect impacts the quality of ratings, pinpoint various indices they have used to measure it, and describe various strategies that have been proposed to try to minimize its impact on the measurement of ratees. The second half of Part 1 provides conceptual and mathematical explanations of many-facet Rasch measurement, focusing on how researchers can use MFRM to study rater effects. First, we present the many-facet version of Andrich's (1978) rating scale model and identify questions about a rating operation that researchers can address using this model. We then introduce three hybrid MFRM models, explain the conceptual distinctions among them, describe how they differ from the rating scale model, and identify questions about a rating operation that researchers can address using these hybrid models.     

Comparing holistic and analytic scoring for performance assessment with many-facet Rasch model

This paper compares holistic and analytic scoring methods to explore how the alternative scorings can make differences for performance assessment using many-faceted Rasch model. The model is especially pertinent for analyzing performance assessment since the model can include several facets simultaneously. Forty three students' reports for social studies were scored by four raters with the holistic method and the analytic method. The result demonstrated that scoring rubrics could be improved by investigating rating scale categories. Also, the comparison of student scores between the two scoring methods revealed that the selection of scoring methods might not be significant for the relative comparison of students but it could have serious implication for the assessment of students' absolute abilities. For rater severity, analytic scoring provided more consistency than holistic scoring. These findings can be used to select and improve scoring methods for performance assessment.     

Detecting and measuring rater effects using many-facet Rasch measurement: Part II

The purpose of this two-part paper is to introduce researchers to the many-facet Rasch measurement (MFRM) approach for detecting and measuring rater effects. In Part II of the paper, researchers will learn how to use the Facets (Linacre, 2001) computer program to study five effects: leniency/severity, central tendency, randomness, halo, and differential leniency/severity. As we introduce each effect, we operationally define it within the context of a MFRM approach, specify the particular measurement model(s) needed to detect it, identify group- and individual-level statistical indicators of the effect, and show output from a Facets analysis, pinpointing the various indicators and explaining how to interpret each one. At the close of the paper, we describe other statistical procedures that have been used to detect and measure rater effects to help researchers become aware of important and influential literature on the topic and to gain an appreciation for the diversity of psychometric perspectives that researchers bring to bear on their work. Finally, we consider future directions for research in the detection and measurement of rater effects.     

Auto-association measures for stationary time series of categorical data

For stationary time series of nominal categorical data or ordinal categorical data (with arbitrary ordered numberings of the categories), autocorrelation does not make much sense. Biswas and Guha (J Stat Plan Infer 139:3076–3087, 2009a) used mutual information as a measure of association and introduced the concept of auto-mutual information in this context. In this present paper, we introduce general auto-association measures for this purpose and study several special cases. Theoretical properties and simulation results are given along with two illustrative real data examples.     

Testing of multivariate repeated measures data with block exchangeable covariance structure

A new hypothesis testing of equality of mean vectors in two populations using \(D^2\) statistic for multivariate repeated measures data on q response variables at p sites or time points in a block exchangeable covariance matrix setting is proposed. The minimum sample size needed for our new test is only \(q +1\), unlike \(pq +1\) in Hotelling’s \(T^2\) test. The new test is very efficient in small sample scenario, when the number of observations is not adequate to estimate the \(pq \times pq\) dimensional unknown unstructured variance–covariance matrix. Some simulation studies are performed to compare the power of the new \(D^2\) test and the existing \(BT^2\) test. The performance of the proposed \(D^2\) test is demonstrated with the two medical data sets.     

西部铁路通道建设及政策措施

在分析西部铁路客货运输需求的基础上,提出目前存在的主要问题,强调了建设铁路运输通道的必要性。阐明了西部铁路网发展目标、铁路通道建设原则,以及区域通道、内部通道、国际通道等主要建设项目规划,并提出了加快西部铁路通道建设的若干政策措施。     

Mutual fund performance evaluation using data envelopment analysis with new risk measures

The data envelopment analysis (DEA) technique has been found very useful for evaluating the mutual fund performance. This applied study extends previous results in two ways: to properly reflect the pervasive skewness and leptokurtosis in return distributions of actively managed funds, new risk measures value-at-risk (VaR) and conditional value-at-risk (CVaR) are introduced into inputs of the existing DEA models; to fairly evaluate the relative performance of the same fund during different time periods, we creatively treat the same fund during different periods as different decision making units. Except for confirming current empirical conclusions, detailed empirical analyses using data of the Chinese mutual fund market show that, VaR and CVaR, especially their combinations with traditional risk measures, are very helpful for comprehensively describing return distribution properties and fund characteristics such as the asset allocation structure, which, in turn, can better evaluate the overall performance of mutual funds. Treating the same fund during different time periods as different funds can not only show the specific performance variation, but reveal the reasons for that variation.

Global reconstruction from nonstationary data

One-dimensional time series of a dynamical system with slowly varying parameters are investigated. For estimation of the characteristics of the attractors of such a system which exist for fixed values of the parameters, it is proposed to “cut out” from the time series short segments that belong to the individual attractors and to use them to reconstruct a model dynamical system. Pis’ma Zh. Tekh. Fiz. 25, 74–81 (May 26, 1999)     

Shape reconstruction from gradient data

We present a generalized method for reconstructing the shape of an object from measured gradient data. A certain class of optical sensors does not measure the shape of an object but rather its local slope. These sensors display several advantages, including high information efficiency, sensitivity, and robustness. For many applications, however, it is necessary to acquire the shape, which must be calculated from the slopes by numerical integration. Existing integration techniques show drawbacks that render them unusable in many cases. Our method is based on an approximation employing radial basis functions. It can be applied to irregularly sampled, noisy, and incomplete data, and it reconstructs surfaces both locally and globally with high accuracy.     

Comparing clinical automated,medical record,and hybrid data sources for diabetes quality measures

BACKGROUND: Little is known about the relative reliability of medical record and clinical automated data, sources commonly used to assess diabetes quality of care. The agreement between diabetes quality measures constructed from clinical automated versus medical record data sources was compared, and the performance of hybrid measures derived from a combination of the two data sources was examined. METHODS: Medical records were abstracted for 1,032 patients with diabetes who received care from 21 facilities in 4 Veterans Integrated Service Networks. Automated data were obtained from a central Veterans Health Administration diabetes registry containing information on laboratory tests and medication use. RESULTS: Success rates were higher for process measures derived from medical record data than from automated data, but no substantial differences among data sources were found for the intermediate outcome measures. Agreement for measures derived from the medical record compared with automated data was moderate for process measures but high for intermediate outcome measures. Hybrid measures yielded success rates similar to those of medical record-based measures but would have required about 50% fewer chart reviews. CONCLUSIONS: Agreement between medical record and automated data was generally high. Yet even in an integrated health care system with sophisticated information technology, automated data tended to underestimate the success rate in technical process measures for diabetes care and yielded different quartile performance rankings for facilities. Applying hybrid methodology yielded results consistent with the medical record but required less data to come from medical record reviews.     

Reconstruction of parent grains from EBSD data

The limits of the parent grain reconstruction by the neighbor-to-neighbor method are shown. A new method of parent grain reconstruction from EBSD data is proposed for any phase transformation. It is based on the theoretical groupoid structure formed by the variants and their operators. It tolerates materials with high levels of intragranular deformation. It is quick and robust because it does not imply solving any equation, and mainly consists in the comparison of numbers. It has satisfactorily been applied to the reconstruction of austenitic grains in martensitic steels.     

Assessment of dose from faecal measurement data

At AWE, an annual faecal sample forms part of the internal monitoring strategy for insoluble forms of plutonium. The setting of a derived investigation level (DIL) and assessment of doses from results for faecal samples can pose some difficulties in view of uncertainties related to: (a) the time and number of intakes during the monitoring period and (b) the result from a single sample. This paper uses Monte Carlo simulation to investigate the activity that would be expected in faeces following varying numbers of intake events during the monitoring period. The variation in faecal activity of a long-term excretor is also investigated. The implications of the results for the setting of the DIL and assessment of dose are discussed.     

Reconstruction of gratings from noisy reflection data

The worst-case error amplification factor in reconstructing a grating from its complex reflection spectrum is shown to be of the order 1/T(min), where T(min) is the minimum transmissivity through the grating. For a uniform grating with coupling coefficient-length product kappaL, the error amplification is exp(2kappaL). The exponential dependence on the grating strength shows that spatial characterization of gratings from a measured reflection spectrum is impossible if the grating is sufficiently strong. For moderately strong gratings, a simple regularization technique is proposed to stabilize the solution of the inverse-scattering problem of computing the grating structure from the reflection spectrum.     

Estimation of radiation-source coordinates from satellite-observation data

An algorithm is developed for precision evaluation of optical-radiation-source coordinates from satellite-observation data. The results of a numerical experiment confirm its effectiveness and possibility of use in space metrology. Translated from Izmeritel'naya Tekhnika, No. 7, pp. 3–8, July, 2000.     

Determination of thermal diffusivity from experimental data

An algorithm is discussed for determining the temperature dependence of the thermal diffusivity from thermocouple measurements at one or more points within a body.Translated from Inzhenerno-Fizicheskii Zhurnal, Vol. 29, No. 1, pp. 87–90, July, 1975.