133 research outputs found

    Ecological Panel Inference from Repeated Cross Sections

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    Inferring transition probabilities from repeated cross sections: a cross-level inference approach to US presidential voting

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    This paper outlines a nonstationary, heterogeneous Markov model designed to estimate entry and exit transition probabilities at the micro-level from a time series of independent cross-sectional samples with a binary outcome variable. The model has its origins in the work of Moffitt (1993) and shares features with standard statistical methods for ecological inference. We show how ML estimates of the parameters can be obtained by the method-of- scoring, how to estimate time-varying covariate effects, and how to include non-backcastable variables in the model. The latter extension of the basic model is an important one as it strongly increases its potential application in a wide array of research contexts. The example illustration uses survey data on American presidential vote intentions from a five-wave panel study conducted by Patterson (1980) in 1976. We treat the panel data as independent cross sections and compare the estimates of the Markov model with the observations in the panel. Directions for future work are discussed

    Ecological panel inference in repeated cross sections

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    This paper presents a Markov chain model for the estimation of individual-level binary transitions from a time series of independent repeated cross-sectional (RCS) samples. Although RCS samples lack direct information on individual turnover, it is demonstrated here that it is possible with these data to draw meaningful conclusions on individual state-to-state transitions. We discuss estimation and inference using maximum likelihood, parametric bootstrap and Markov chain Monte Carlo approaches. The model is illustrated by an application to the rise in ownership of computers in Dutch households since 1986, using a 13-wave annual panel data set. These data encompass more information than we need to estimate the model, but this additional information allows us to assess the validity of the parameter estimates. We examine the determinants of the transitions from 'have-not' to 'have' (and back again) using well-known socio-economic and demographic covariates of the digital divide. Parametric bootstrap and Bayesian simulation are used to evaluate the accuracy and the precision of the ML estimates and the results are also compared with those of a first-order dynamic panel model. To mimic genuine repeated cross-sectional data, we additionally analyse samples of independent observations randomly drawn from the panel. Software implementing the model is available

    Better poll sampling would have cast more doubt on the potential for Hillary Clinton to win the 2016 election

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    Donald Trump's 2016 election victory took many by surprise - most of the polling had suggested a victory for Hillary Clinton. But were the polls wrong? In new research Manfred te Grotenhuis, Subu Subramanian, Rense Nieuwenhuis, Ben Pelzer and Rob Eisinga examine the election polls' accuracy by randomly sampling from each state's observed voters for Clinton or Trump. They find that a relatively small polling bias which saw Republicans underrepresented in a number of key states tipped the polling – and therefore the predicted probability that she would win – in favor of Hillary Clinton

    Interviewer BMI effects on under- and over-reporting of restrained eating: evidence from a national Dutch face-to-face survey and a postal follow-up

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    Contains fulltext : 102650pub.pdf (publisher's version ) (Open Access)Objectives To determine the effect of interviewer BMI on self-reported restrained eating in a face-to-face survey and to examine under- and over-reporting using the face-to face study and a postal follow-up. Methods A sample of 1,212 Dutch adults was assigned to 98 interviewers with different BMI who administered an eating questionnaire. To further evaluate misreporting a mail follow-up was conducted among 504 participants. Data were analyzed using two-level hierarchical models. Results Interviewer BMI had a positive effect on restrained eating. Normal weight and pre-obese interviewers obtained valid responses, underweight interviewers stimulated underreporting whereas obese interviewers triggered overreporting. Conclusion In face-to-face interviews self-reported dietary restraint is distorted by interviewer BMI. This result has implications for public health surveys, the more so given the expanding obesity epidemic.5 p

    Measurement of the inclusive and dijet cross-sections of b-jets in pp collisions at sqrt(s) = 7 TeV with the ATLAS detector

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    The inclusive and dijet production cross-sections have been measured for jets containing b-hadrons (b-jets) in proton-proton collisions at a centre-of-mass energy of sqrt(s) = 7 TeV, using the ATLAS detector at the LHC. The measurements use data corresponding to an integrated luminosity of 34 pb^-1. The b-jets are identified using either a lifetime-based method, where secondary decay vertices of b-hadrons in jets are reconstructed using information from the tracking detectors, or a muon-based method where the presence of a muon is used to identify semileptonic decays of b-hadrons inside jets. The inclusive b-jet cross-section is measured as a function of transverse momentum in the range 20 < pT < 400 GeV and rapidity in the range |y| < 2.1. The bbbar-dijet cross-section is measured as a function of the dijet invariant mass in the range 110 < m_jj < 760 GeV, the azimuthal angle difference between the two jets and the angular variable chi in two dijet mass regions. The results are compared with next-to-leading-order QCD predictions. Good agreement is observed between the measured cross-sections and the predictions obtained using POWHEG + Pythia. MC@NLO + Herwig shows good agreement with the measured bbbar-dijet cross-section. However, it does not reproduce the measured inclusive cross-section well, particularly for central b-jets with large transverse momenta.Comment: 10 pages plus author list (21 pages total), 8 figures, 1 table, final version published in European Physical Journal

    Search for dark matter produced in association with bottom or top quarks in √s = 13 TeV pp collisions with the ATLAS detector