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Elizabeth L Ogburn, Junhui Cai, Arun K Kuchibhotla, Richard A Berk and Andreas Buja’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes

Ogburn 等对《广义线性模型参数的弱假设推断》的讨论

Not all conditional associations between outcomes and exposures are of interest. Those that are tend to be directional: up or down. The simplest way to assess directionality is to fit a confounder- adjusted linear exposure term, as the authors propose. We agree with this approach as some of us have argued that linear slopes are meaningful and interpretable even if the directional association is not linear (Buja et al., 2019, section 10). The authors, and Whitney et al.…

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Andreas Buja, Richard A. Berk, Arun K. Kuchibhotla, Linda Zhao and Ed George’s Contribution to the Discussion of ‘Assumption-Lean Inference for Generalised Linear Model Parameters’ by Vansteelandt and Dukes

Buja 等对“广义线性模型参数的弱假设推断”的讨论

We thank the authors for their stimulating article. At the highest level, it agrees with our thinking as expressed in the second of two articles in Statistical Science (Buja et al., 2019). The guiding principle is to focus on quantities of interest that are meaningful statistical functionals, beyond the statistical models that motivate them, even when those models are fully misspecified. In some form, this focus has existed for decades in the semi-parametric literature. We…

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An Evaluation of California's Inmate Classification System Using a Generalized Regression Discontinuity Design

用广义断点回归设计评估加利福尼亚州囚犯分类系统

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

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An Evaluation of California's Inmate Classification System Using a Generalized Regression Discontinuity Design

用广义断点回归设计评估加州囚犯分类制度

Published studies using the regression discontinuity design have been limited to cases in which linear regression is applied to a categorical treatment indicator and an equal interval outcome. This is unnecessarily narrow. We show here how a generalization the usual regression discontinuity design can be applied in a wider range of situations. We focus on the use of categorical treatment and response variables, but we also consider the more general case of any regression…

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Capitalizing on Nonrandom Assignment to Treatments: A Regression-Discontinuity Evaluation of a Crime-Control Program

利用非随机处理分配:犯罪控制项目的断点回归评估

Despite the enormous potential of regression-discontinuity, quasi-experimental procedures, they have to date rarely been used in the evaluation of large-scale social programs. In this article, we report an evaluation of such a program in which a regression-discontinuity analysis is employed. Through a change in legislation, the program in question extended eligibility for unemployment benefits to prisoners after their release from prison. The regression-discontinuity…

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