3,468 research outputs found
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
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