281 research outputs found
Multiple Imputation for Incomplete Data in Epidemiologic Studies
Epidemiologic studies are frequently susceptible to missing information. Omitting observations with missing variables remains a common strategy in epidemiologic studies, yet this simple approach can often severely bias parameter estimates of interest if the values are not missing completely at random. Even when missingness is completely random, complete-case analysis can reduce the efficiency of estimated parameters, because large amounts of available data are simply tossed out with the incomplete observations. Alternative methods for mitigating the influence of missing information, such as multiple imputation, are becoming an increasing popular strategy in order to retain all available information, reduce potential bias, and improve efficiency in parameter estimation. In this paper, we describe the theoretical underpinnings of multiple imputation, and we illustrate application of this method as part of a collaborative challenge to assess the performance of various techniques for dealing with missing data (Am J Epidemiol. 2018;187(3):568–575). We detail the steps necessary to perform multiple imputation on a subset of data from the Collaborative Perinatal Project (1959–1974), where the goal is to estimate the odds of spontaneous abortion associated with smoking during pregnancy
Inverse-Probability-Weighted Estimation for Monotone and Nonmonotone Missing Data
Missing data is a common occurrence in epidemiologic research. In this paper, 3 data sets with induced missing values from the Collaborative Perinatal Project, a multisite US study conducted from 1959 to 1974, are provided as examples of prototypical epidemiologic studies with missing data. Our goal was to estimate the association of maternal smoking behavior with spontaneous abortion while adjusting for numerous confounders. At the same time, we did not necessarily wish to evaluate the joint distribution among potentially unobserved covariates, which is seldom the subject of substantive scientific interest. The inverse probability weighting (IPW) approach preserves the semiparametric structure of the underlying model of substantive interest and clearly separates the model of substantive interest from the model used to account for the missing data. However, IPW often will not result in valid inference if the missing-data pattern is nonmonotone, even if the data are missing at random. We describe a recently proposed approach to modeling nonmonotone missing-data mechanisms under missingness at random to use in constructing the weights in IPW complete-case estimation, and we illustrate the approach using 3 data sets described in a companion article (Am J Epidemiol. 2018;187(3):568–575)
Principled Approaches to Missing Data in Epidemiologic Studies
Principled methods with which to appropriately analyze missing data have long existed; however, broad implementation of these methods remains challenging. In this and 2 companion papers (Am J Epidemiol. 2018;187(3):576–584 and Am J Epidemiol. 2018;187(3):585–591), we discuss issues pertaining to missing data in the epidemiologic literature. We provide details regarding missing-data mechanisms and nomenclature and encourage the conduct of principled analyses through a detailed comparison of multiple imputation and inverse probability weighting. Data from the Collaborative Perinatal Project, a multisite US study conducted from 1959 to 1974, are used to create a masked data-analytical challenge with missing data induced by known mechanisms. We illustrate the deleterious effects of missing data with naive methods and show how principled methods can sometimes mitigate such effects. For example, when data were missing at random, naive methods showed a spurious protective effect of smoking on the risk of spontaneous abortion (odds ratio (OR) = 0.43, 95% confidence interval (CI): 0.19, 0.93), while implementation of principled methods multiple imputation (OR = 1.30, 95% CI: 0.95, 1.77) or augmented inverse probability weighting (OR = 1.40, 95% CI: 1.00, 1.97) provided estimates closer to the “true” full-data effect (OR = 1.31, 95% CI: 1.05, 1.64). We call for greater acknowledgement of and attention to missing data and for the broad use of principled missing-data methods in epidemiologic research
Scale-free memory model for multiagent reinforcement learning. Mean field approximation and rock-paper-scissors dynamics
A continuous time model for multiagent systems governed by reinforcement
learning with scale-free memory is developed. The agents are assumed to act
independently of one another in optimizing their choice of possible actions via
trial-and-error search. To gain awareness about the action value the agents
accumulate in their memory the rewards obtained from taking a specific action
at each moment of time. The contribution of the rewards in the past to the
agent current perception of action value is described by an integral operator
with a power-law kernel. Finally a fractional differential equation governing
the system dynamics is obtained. The agents are considered to interact with one
another implicitly via the reward of one agent depending on the choice of the
other agents. The pairwise interaction model is adopted to describe this
effect. As a specific example of systems with non-transitive interactions, a
two agent and three agent systems of the rock-paper-scissors type are analyzed
in detail, including the stability analysis and numerical simulation.
Scale-free memory is demonstrated to cause complex dynamics of the systems at
hand. In particular, it is shown that there can be simultaneously two modes of
the system instability undergoing subcritical and supercritical bifurcation,
with the latter one exhibiting anomalous oscillations with the amplitude and
period growing with time. Besides, the instability onset via this supercritical
mode may be regarded as "altruism self-organization". For the three agent
system the instability dynamics is found to be rather irregular and can be
composed of alternate fragments of oscillations different in their properties.Comment: 17 pages, 7 figur
Longitudinal double-spin asymmetry and cross section for inclusive neutral pion production at midrapidity in polarized proton collisions at sqrt(s) = 200 GeV
We report a measurement of the longitudinal double-spin asymmetry A_LL and
the differential cross section for inclusive Pi0 production at midrapidity in
polarized proton collisions at sqrt(s) = 200 GeV. The cross section was
measured over a transverse momentum range of 1 < p_T < 17 GeV/c and found to be
in good agreement with a next-to-leading order perturbative QCD calculation.
The longitudinal double-spin asymmetry was measured in the range of 3.7 < p_T <
11 GeV/c and excludes a maximal positive gluon polarization in the proton. The
mean transverse momentum fraction of Pi0's in their parent jets was found to be
around 0.7 for electromagnetically triggered events.Comment: 6 pages, 3 figures, submitted to Phys. Rev. D (RC
Implementation Evaluation of a Complex Intervention to Improve Timeliness of Care for Veterans with Transient Ischemic Attack
Background: The Protocol-guided Rapid Evaluation of Veterans Experiencing New Transient Neurologic Symptoms (PREVENT) program was designed to address systemic barriers to providing timely guideline-concordant care for patients with transient ischemic attack (TIA).
Objective: We evaluated an implementation bundle used to promote local adaptation and adoption of a multi-component, complex quality improvement (QI) intervention to improve the quality of TIA care Bravata et al. (BMC Neurology 19:294, 2019).
Design: A stepped-wedge implementation trial with six geographically diverse sites.
Participants: The six facility QI teams were multi-disciplinary, clinical staff.
Interventions: PREVENT employed a bundle of key implementation strategies: team activation; external facilitation; and a community of practice. This strategy bundle had direct ties to four constructs from the Consolidated Framework for Implementation Research (CFIR): Champions, Reflecting & Evaluating, Planning, and Goals & Feedback.
Main measures: Using a mixed-methods approach guided by the CFIR and data matrix analyses, we evaluated the degree to which implementation success and clinical improvement were associated with implementation strategies. The primary outcomes were the number of completed implementation activities, the level of team organization and > 15 points improvement in the Without Fail Rate (WFR) over 1 year.
Key results: Facility QI teams actively engaged in the implementation strategies with high utilization. Facilities with the greatest implementation success were those with central champions whose teams engaged in planning and goal setting, and regularly reflected upon their quality data and evaluated their progress against their QI plan. The strong presence of effective champions acted as a pre-condition for the strong presence of Reflecting & Evaluating, Goals & Feedback, and Planning (rather than the other way around), helping to explain how champions at the +2 level influenced ongoing implementation.
Conclusions: The CFIR-guided bundle of implementation strategies facilitated the local implementation of the PREVENT QI program and was associated with clinical improvement in the national VA healthcare system
Measurement of the Bottom contribution to non-photonic electron production in collisions at =200 GeV
The contribution of meson decays to non-photonic electrons, which are
mainly produced by the semi-leptonic decays of heavy flavor mesons, in
collisions at 200 GeV has been measured using azimuthal
correlations between non-photonic electrons and hadrons. The extracted
decay contribution is approximately 50% at a transverse momentum of GeV/. These measurements constrain the nuclear modification factor for
electrons from and meson decays. The result indicates that meson
production in heavy ion collisions is also suppressed at high .Comment: 6 pages, 4 figures, accepted by PR
Longitudinal scaling property of the charge balance function in Au + Au collisions at 200 GeV
We present measurements of the charge balance function, from the charged
particles, for diverse pseudorapidity and transverse momentum ranges in Au + Au
collisions at 200 GeV using the STAR detector at RHIC. We observe that the
balance function is boost-invariant within the pseudorapidity coverage [-1.3,
1.3]. The balance function properly scaled by the width of the observed
pseudorapidity window does not depend on the position or size of the
pseudorapidity window. This scaling property also holds for particles in
different transverse momentum ranges. In addition, we find that the width of
the balance function decreases monotonically with increasing transverse
momentum for all centrality classes.Comment: 6 pages, 3 figure
Inflation and Braneworlds: Degeneracies and Consistencies
Scalar and tensor perturbations arising in an inflationary braneworld
scenario driven by a single scalar field are considered, where the bulk on
either side of the brane corresponds to Anti-de Sitter spaces with different
cosmological constants. A consistency relation between the two spectra is
derived and found to have an identical form to that arising in standard
single-field inflation based on conventional Einstein gravity. The dS/CFT
correspondence may provide further insight into the origin of this degeneracy.
Possible ways of lifting such a degeneracy are discussed.Comment: 10 page
Association of genetic susceptibility variants for type 2 diabetes with breast cancer risk in women of European ancestry.
Purpose: Type 2 diabetes (T2D) has been reported to be associated with an elevated risk of breast cancer. It is unclear, however, whether this association is due to shared genetic factors.
Methods: We constructed a genetic risk score (GRS) using risk variants from 33 known independent T2D susceptibility loci and evaluated its relation to breast cancer risk using the data from two consortia, including 62,328 breast cancer patients and 83,817 controls of European ancestry. Unconditional logistic regression models were used to derive adjusted odds ratios (ORs) and 95 % confidence intervals (CIs) to measure the association of breast cancer risk with T2D GRS or T2D-associated genetic risk variants. Meta-analyses were conducted to obtain summary ORs across all studies.
Results: The T2D GRS was not found to be associated with breast cancer risk, overall, by menopausal status, or for estrogen receptor positive or negative breast cancer. Three T2D associated risk variants were individually associated with breast cancer risk after adjustment for multiple comparisons using the Bonferroni method (at p < 0.001), rs9939609 (FTO) (OR 0.94, 95 % CI = 0.92–0.95, p = 4.13E−13), rs7903146 (TCF7L2) (OR 1.04, 95 % CI = 1.02–1.06, p = 1.26E−05), and rs8042680 (PRC1) (OR 0.97, 95 % CI = 0.95–0.99, p = 8.05E−04).
Conclusions: We have shown that several genetic risk variants were associated with the risk of both T2D and breast cancer. However, overall genetic susceptibility to T2D may not be related to breast cancer risk
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