Computing Inter-Rater Reliability for Observational Data: An Overview and Tutorial

Many research designs require the assessment of inter-rater reliability (IRR) to demonstrate consistency among observational ratings provided by multiple coders. However, many studies use incorrect statistical procedures, fail to fully report the information necessary to interpret their results, or do not address how IRR affects the power of their subsequent analyses for hypothesis testing. This paper provides an overview of methodological issues related to the assessment of IRR with a focus on study design, selection of appropriate statistics, and the computation, interpretation, and reporting of some commonly-used IRR statistics. Computational examples include SPSS and R syntax for computing Cohens kappa and intra-class correlations to assess IRR

Conducting Simulation Studies in the R Programming Environment

Simulation studies allow researchers to answer specific questions about data analysis, statistical power, and best-practices for obtainingaccurate results in empirical research. Despite the benefits that simulation research can provide, many researchers are unfamiliar with available tools for conducting their own simulation studies. The use of simulation studies need not be restricted toresearchers with advanced skills in statistics and computer programming, and such methods can be implemented by researchers with a variety of abilities and interests. The present paper provides an introduction to methods used for running simulationstudies using the R statistical programming environment and is written for individuals with minimal experience running simulation studies or using R. The paper describes the rationale and benefits of using simulations and introduces R functions relevant for many simulation studies. Three examples illustrate different applications for simulation studies, including (a) the use of simulations to answer a novel question about statistical analysis, (b) the use of simulations to estimate statistical power, and (c) the use of simulations to obtain confidence intervals of parameter estimates throughbootstrapping. Results and fully annotated syntax from these examples are provided

Physics Results from the AMANDA-B10 Neutrino Telescope

The data from the first year of operation of the 10-string, AMANDA-B10, high-energy neutrino detector array at the South Pole have been analyzed and searched for evidence of neutrinos from cosmic sources. Differently optimized selection criteria have been used and limits on the flux of high-energy neutrinos from a variety of objects have been derivedComment: 3 pages, 3 figures, presented at TAUP 2001, LNGS/Italy, September 2001. Fig. 3 updated and reference correcte

Changepoint detection on a graph of time series

When analysing multiple time series that may be subject to changepoints, it is sometimes possible to specify a priori, by means of a graph G, which pairs of time series are likely to be impacted by simultaneous changepoints. This article proposes a novel Bayesian changepoint model for multiple time series that borrows strength across clusters of connected time series in G to detect weak signals for synchronous changepoints. The graphical changepoint model is further extended to allow dependence between nearby but not necessarily synchronous changepoints across neighbour time series in G. A novel reversible jump MCMC algorithm making use of auxiliary variables is proposed to sample from the graphical changepoint model. The merit of the proposed model is demonstrated via a changepoint analysis of real network authentication data from Los Alamos National Laboratory (LANL), with some success at detecting weak signals for network intrusions across users that are linked by network connectivity, whilst limiting the number of false alerts.Comment: 31 pages, 13 figure

An efficient quantum algorithm for the hidden subgroup problem in extraspecial groups

Extraspecial groups form a remarkable subclass of p-groups. They are also present in quantum information theory, in particular in quantum error correction. We give here a polynomial time quantum algorithm for finding hidden subgroups in extraspecial groups. Our approach is quite different from the recent algorithms presented in [17] and [2] for the Heisenberg group, the extraspecial p-group of size p3 and exponent p. Exploiting certain nice automorphisms of the extraspecial groups we define specific group actions which are used to reduce the problem to hidden subgroup instances in abelian groups that can be dealt with directly.Comment: 10 page

Including Systematic Uncertainties in Confidence Interval Construction for Poisson Statistics

One way to incorporate systematic uncertainties into the calculation of confidence intervals is by integrating over probability density functions parametrizing the uncertainties. In this note we present a development of this method which takes into account uncertainties in the prediction of background processes, uncertainties in the signal detection efficiency and background efficiency and allows for a correlation between the signal and background detection efficiencies. We implement this method with the Feldman & Cousins unified approach with and without conditioning. We present studies of coverage for the Feldman & Cousins and Neyman ordering schemes. In particular, we present two different types of coverage tests for the case where systematic uncertainties are included. To illustrate the method we show the relative effect of including systematic uncertainties the case of dark matter search as performed by modern neutrino tel escopes.Comment: 23 pages, 10 figures, replaced to match published versio

An Introduction to Quantum Programming in Quipper

Quipper is a recently developed programming language for expressing quantum computations. This paper gives a brief tutorial introduction to the language, through a demonstration of how to make use of some of its key features. We illustrate many of Quipper's language features by developing a few well known examples of Quantum computation, including quantum teleportation, the quantum Fourier transform, and a quantum circuit for addition.Comment: 15 pages, RC201

Impact on adolescent mental health of replacing screen-use with exercise: A prospective cohort study

BACKGROUND: Screen-based device use could increase the risk of adolescent depression. Distinct modalities of screen-use may have differential effects on mental health. We used compositional data analysis to examine how theoretically replacing different screen-uses with exercise might influence future adolescent emotional distress. METHODS: In 4,599 adolescents (55% female) from a nationally-representative, prospective cohort, we used time-use diary data at age 14 to estimate daily screen use (television, social media, video game, general computer use) and exercise (team sport and individual exercise). The outcome was emotional distress at age 17, assessed using the emotional symptoms subscale of the Strengths and Difficulties Questionnaire. RESULTS: Theoretically replacing 60 minutes of total screen time with exercise at age 14 was associated with a 0.05 (95%CI -0.08, -0.02) score reduction on the emotional symptoms' subscale at 17 in fully-adjusted models. Replacing 60 minutes of television or social media use with team sports was associated with a reduction of 0.17 (95%CI, -0.31, -0.04) and 0.15 (95%CI, -0.29, -0.01) in emotional symptom scores, respectively. We found no change in emotional symptom scores when replacing video game or general computer use with team sport, or when replacing any screen time with individual exercise. LIMITATIONS: No direct measure of depressive symptoms at follow-up. CONCLUSIONS: Replacing any screen time with exercise could reduce emotional distress, but the largest effect sizes were associated with replacing time in television watching and social media with team sports. Recommendations to limit screen-use in adolescents may require a nuanced approach for protecting mental health