A note on applying the BCH method under linear equality and inequality constraints

Researchers often wish to relate estimated scores on latent variables to exogenous covariates not previously used in analyses. The BCH method corrects for asymptotic bias in estimates due to these scores’ uncertainty and has been shown to be relatively robust. When applying the BCH approach however, two problems arise. First, negative cell proportions can be obtained. Second, the approach cannot deal with situations where marginals need to be fixed to specific values, such as edit restrictions. The BCH approach can handle these problems when placed in a framework of quadratic loss functions and linear equality and inequality constraints. This research note gives the explicit form for equality constraints and demonstrates how solutions for inequality constraints may be obtained using numerical methods

Human Data Science

Most data science is about people, and opinions on the value of human data differ. The author offers a synthesis of overly optimistic and overly pessimistic views of human data science: it should become a science, with errors systematically studied and their effects mitigated—a goal that can only be achieved by bringing together expertise from a range of disciplines. Most data science is about people, and opinions on the value of human data differ. The author offers a synthesis of overly optimistic and overly pessimistic views of human data science: it should become a science, with errors systematically studied and their effects mitigated—a goal that can only be achieved by bringing together expertise from a range of disciplines

GRAIL, an omni-directional gravitational wave detector

A cryogenic spherical and omni-directional resonant-mass detector proposed by the GRAIL collaboration is described.Comment: 5 pages, 4 figs., contribution to proceedings GW Data Analysis Workshop, Paris, nov. 199

Automatic multilabel detection of ICD10 codes in Dutch cardiology discharge letters using neural networks

Standard reference terminology of diagnoses and risk factors is crucial for billing, epidemiological studies, and inter/intranational comparisons of diseases. The International Classification of Disease (ICD) is a standardized and widely used method, but the manual classification is an enormously time-consuming endeavor. Natural language processing together with machine learning allows automated structuring of diagnoses using ICD-10 codes, but the limited performance of machine learning models, the necessity of gigantic datasets, and poor reliability of terminal parts of these codes restricted clinical usability. We aimed to create a high performing pipeline for automated classification of reliable ICD-10 codes in the free medical text in cardiology. We focussed on frequently used and well-defined three- and four-digit ICD-10 codes that still have enough granularity to be clinically relevant such as atrial fibrillation (I48), acute myocardial infarction (I21), or dilated cardiomyopathy (I42.0). Our pipeline uses a deep neural network known as a Bidirectional Gated Recurrent Unit Neural Network and was trained and tested with 5548 discharge letters and validated in 5089 discharge and procedural letters. As in clinical practice discharge letters may be labeled with more than one code, we assessed the single- and multilabel performance of main diagnoses and cardiovascular risk factors. We investigated using both the entire body of text and only the summary paragraph, supplemented by age and sex. Given the privacy-sensitive information included in discharge letters, we added a de-identification step. The performance was high, with F1 scores of 0.76–0.99 for three-character and 0.87–0.98 for four-character ICD-10 codes, and was best when using complete discharge letters. Adding variables age/sex did not affect results. For model interpretability, word coefficients were provided and qualitative assessment of classification was manually performed. Because of its high performance, this pipeline can be useful to decrease the administrative burden of classifying discharge diagnoses and may serve as a scaffold for reimbursement and research applications

Understanding Society Innovation Panel Wave 8: results from methodological experiments

This paper presents some preliminary findings from Wave 8 of the Innovation Panel (IP8) of Understanding Society: The UK Household Longitudinal Study. Understanding Society is a major panel survey in the UK. May 2015, the eighth wave of the Innovation Panel went into the field. IP8 used a mixed-mode design, using on-line interviews and face-to-face interviews. This paper describes the design of IP8, the experiments carried and the preliminary findings from early analysis of the data

Measurement of mechanical vibrations excited in aluminium resonators by 0.6 GeV electrons

We present measurements of mechanical vibrations induced by 0.6 GeV electrons impinging on cylindrical and spherical aluminium resonators. To monitor the amplitude of the resonator's vibrational modes we used piezoelectric ceramic sensors, calibrated by standard accelerometers. Calculations using the thermo-acoustic conversion model, agree well with the experimental data, as demonstrated by the specific variation of the excitation strengths with the absorbed energy, and with the traversing particles' track positions. For the first longitudinal mode of the cylindrical resonator we measured a conversion factor of 7.4 +- 1.4 nm/J, confirming the model value of 10 nm/J. Also, for the spherical resonator, we found the model values for the L=2 and L=1 mode amplitudes to be consistent with our measurement. We thus have confirmed the applicability of the model, and we note that calculations based on the model have shown that next generation resonant mass gravitational wave detectors can only be expected to reach their intended ultra high sensitivity if they will be shielded by an appreciable amount of rock, where a veto detector can reduce the background of remaining impinging cosmic rays effectively.Comment: Tex-Article with epsfile, 34 pages including 13 figures and 5 tables. To be published in Rev. Scient. Instr., May 200