Results 61 to 70 of about 16,361 (164)
Shaking the trees: Abilities and Capabilities of Regression and Decision Trees for Political Science
ITM Web of Conferences, 2017 When committing to quantitative political science, a researcher has a wealth of methods to choose from. In this paper we compare the established method of analyzing roll call data using W-NOMINATE scores to a data-driven supervised machine learning ...
Waldhauser Christoph, Hochreiter Ronald
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Jailbreaking as a Reward Misspecification Problem
CoRRAccepted to ICLR 2025.
Zhihui Xie 0002 +5 more
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BMC Medical Research MethodologyBackground Causal mediation analysis is widespread in applied medical research, especially in longitudinal settings. However, estimating natural mediational effects in such contexts is often difficult because of the presence of post-treatment confounding.
Chiara Di Maria, Vanessa Didelez
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Genetic model misspecification in genetic association studies
BMC Research Notes, 2017 Objective The underlying model of the genetic determinant of a trait is generally not known with certainty a priori. Hence, in genetic association studies, a dominant model might be erroneously modelled as additive, an error investigated previously.
Amadou Gaye, Sharon K. Davis
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MathematicsPoisson mixed-effects models are essential for analyzing repeated count data, relying on latent random effects to account for unobserved heterogeneity and longitudinal dependence.
Jairo A. Ángel, Jorge I. Vélez
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The relationship between excess returns, firm size and earnings on the Johannesburg Stock Exchange
South African Journal of Business Management, 1991 While considerable empirical work has been conducted in the United States concerning excess returns and the relationship of these returns to firm size and E/P ratio, thus far, there have been few similar empirical studies conducted using Johannesburg ...
Michael J. Page, Francis Palmer
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Errors in Statistical Inference Under Model Misspecification: Evidence, Hypothesis Testing, and AIC
Frontiers in Ecology and Evolution, 2019 The methods for making statistical inferences in scientific analysis have diversified even within the frequentist branch of statistics, but comparison has been elusive.
Brian Dennis +4 more
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Efficient Imitation under Misspecification
CoRRWe consider the problem of imitation learning under misspecification: settings where the learner is fundamentally unable to replicate expert behavior everywhere. This is often true in practice due to differences in observation space and action space expressiveness (e.g. perceptual or morphological differences between robots and humans).
Nicolas A. Espinosa Dice +3 more
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Frontiers in Psychology, 2018 The performance of the limited-information statistic M2 for diagnostic classification models (DCMs) is under-investigated in the current literature. Specifically, the investigations of M2 for specific DCMs rather than general modeling frameworks are ...
Fu Chen, Yanlou Liu, Tao Xin, Ying Cui
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CPT: Pharmacometrics & Systems PharmacologyWe address the problem of model misspecification in population pharmacokinetics (PopPK), by modeling residual unexplained variability (RUV) by machine learning (ML) methods in a postprocessing step after conventional model building. The practical purpose
Christos Kaikousidis +2 more
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