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作者：Eckles, Dean; Ignatiadis, Nikolaos; Wager, Stefan; Wu, Han
作者单位：Massachusetts Institute of Technology (MIT); University of Chicago; University of Chicago; Stanford University
摘要：Regression discontinuity designs assess causal effects in settings where treatment is determined by whether an observed running variable crosses a prespecified threshold. Here, we propose a new approach to identification, estimation and inference in regression discontinuity designs that uses knowledge about exogenous noise (e.g., measurement error) in the running variable. In our strategy, we weight treated and control units to balance a latent variable, of which the running variable is a nois...
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作者：Khan, S.; Ugander, J.
作者单位：Stanford University; Stanford University
摘要：A popular method for variance reduction in causal inference is propensity-based trimming, the practice of removing units with extreme propensities from the sample. This practice has theoretical grounding when the data are homoscedastic and the propensity model is parametric (Crump et al., 2009; Yang & Ding, 2018), but in modern settings where heteroscedastic data are analysed with nonparametric models, existing theory fails to support current practice. In this work, we address this challenge b...
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作者：Agnoletto, D.; Rigon, T.; Dunson, D. B.
作者单位：Duke University; University of Milano-Bicocca
摘要：Generalized linear models are routinely used for modelling relationships between a response variable and a set of covariates. The simple form of a generalized linear model comes with easy interpretability, but also leads to concerns about model misspecification impacting inferential conclusions. A popular semiparametric solution adopted in the frequentist literature is quasilikelihood, which improves robustness by only requiring correct specification of the first two moments. We develop a robu...
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作者：Davis, Richard A.; Fernandes, Leon
作者单位：Columbia University
摘要：A fundamental and often final step in time series modelling is to assess the quality of fit of a proposed model to the data. Since the underlying distribution of the innovations that generate a model is often not prescribed, goodness-of-fit tests typically take the form of testing the fitted residuals for serial independence. However, these fitted residuals are intrinsically dependent since they are based on the same parameter estimates, and thus standard tests of serial independence, such as ...
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作者：Graham, E.; Carone, M.; Rotnitzky, A.
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作者：Bagkavos, D.; Isakson, A.; Mammen, E.; Nielsen, J. P.; Proust-Lima, C.
作者单位：University of Ioannina; University of London; Ruprecht Karls University Heidelberg; University of London; Institut National de la Sante et de la Recherche Medicale (Inserm); Universite de Bordeaux
摘要：We introduce a new concept for forecasting future events based on marker information. The model is developed in the nonparametric counting process setting under the assumptions that the marker is of so-called high quality and with a time-homogeneous conditional distribution. Despite the model having nonparametric parts, it is established herein that it attains a parametric rate of uniform consistency and uniform asymptotic normality. In usual nonparametric scenarios, reaching such a fast conve...
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作者：Zhang, Yiqiao; Ekvall, Karl Oskar; Molstad, Aaron J.
作者单位：State University System of Florida; University of Florida; University of Minnesota System; University of Minnesota Twin Cities
摘要：We show that in a variance component model, confidence intervals with asymptotically correct uniform coverage probability can be obtained by inverting certain test statistics based on the score for the restricted likelihood. The results hold in settings where the variance component is near or at the boundary of the parameter set. Simulations indicate that the proposed test statistics are approximately pivotal and lead to confidence intervals with near-nominal coverage even in small samples. We...
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作者：Rossell, D.; Seong, A. K.; Saez, I.; Guindani, M.
作者单位：Pompeu Fabra University; University of California System; University of California Irvine; Icahn School of Medicine at Mount Sinai; University of California System; University of California Los Angeles
摘要：Local variable selection aims to test for the effect of covariates on an outcome within specific regions. We outline a challenge that arises in the presence of nonlinear effects and model misspecification. Specifically, for common semiparametric methods, even slight model misspecification can result in a high false positive rate, in a manner that is highly sensitive to the chosen basis functions. We propose a method based on orthogonal cut splines that avoids false positive inflation for any c...
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作者：Liu, Changyu; Su, Wen; Liu, Kin-Yat; Yin, Guosheng; Zhao, Xingqiu
作者单位：Chinese University of Hong Kong; City University of Hong Kong; University of Hong Kong; Hong Kong Polytechnic University
摘要：We propose a functional accelerated failure time model to characterize the effects of both functional and scalar covariates on the time to event of interest, and provide regularity conditions to guarantee model identifiability. For efficient estimation of model parameters, we develop a sieve maximum likelihood approach where parametric and nonparametric coefficients are bundled with an unknown baseline hazard function in the likelihood function. Not only do the bundled parameters cause immense...
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作者：Feng, Rui; Leng, Chenlei
作者单位：University of Warwick
摘要：Asymmetric relational data are becoming increasingly prevalent in diverse fields, underscoring the need for developing directed network models to address the complex challenges posed by the unique structure of such data. Unlike undirected models, directed models can capture reciprocity, the tendency of nodes to form mutual links. This work addresses a fundamental question: what is the effective sample size for modelling reciprocity? We examine this question by analysing the Bernoulli model wit...
