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Mendelian randomization indicates causal effects of estradiol levels on kidney function in males
Frontiers in Endocrinology, 2023 ContextChronic kidney disease (CKD) is a public health burden worldwide. Epidemiological studies observed an association between sex hormones, including estradiol, and kidney function.ObjectiveWe conducted a Mendelian randomization (MR) study to assess a
M. Kamal Nasr +9 more
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Causality connectives in Japanese: A translation-based study
Японские исследования, 2023 This paper uses an ad hoc corpus of an acknowledged translation of a play by Anton Chekhov to study means of expressing causality in Russian and Japanese discourse.
S. V. Chironov
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Causal Factors, Causal Inference, Causal Explanation [PDF]
Aristotelian Society Supplementary Volume, 1986 s from how likely it is that the person is a smoker in the first place. More generally, the trouble is that the likelihood principle aims to by-pass decisions about prior probabilities. Perhaps there are some inferential contexts where such decisions can sensibly be avoided. But the inference from Harry's heart attack to his smoking isn't one of them. (
Elliott Sober, David Papineau
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Review of mendelian randomization studies on age at natural menopause
Frontiers in Endocrinology, 2023 Menopause marks the end of the reproductive phase of life. Based on epidemiological studies, abnormal age at natural menopause (ANM) is thought to contribute to a number of adverse outcomes, such as osteoporosis, cardiovascular disease, and cancer ...
Xiao Zhang +6 more
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Frontiers in Genetics, 2023 Observational studies have suggested a positive association between gastroesophageal reflux disease and lung cancer, but due to the existence of confounders, it remains undetermined whether gastroesophageal reflux disease (GERD) has a causal association ...
Jing Yang +6 more
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Causality for Machine Learning [PDF]
Probabilistic and Causal Inference, 2019 Graphical causal inference as pioneered by Judea Pearl arose from research on artificial intelligence (AI), and for a long time had little connection to the field of machine learning.
B. Scholkopf
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The Implicit Causality in Verbs
Scientific Bulletin of the Politehnica University of Timişoara: Transactions on Modern Languages, 2022 Natural languages display a great variety of devices that are used to speak of causal relations, ranging from prepositions, subordinating conjunctions and verbs.
S. Lindemann, Sabina Homana
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Causality, Causal Discovery, and Causal Inference in Structural Engineering
CoRR, 2022 Much of our experiments are designed to uncover the cause(s) and effect(s) behind a data generating mechanism (i.e., phenomenon) we happen to be interested in. Uncovering such relationships allows us to identify the true working of a phenomenon and, most importantly, articulate a model that may enable us to further explore the phenomenon on hand and/or
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A homogeneous approach to testing for Granger non-causality in heterogeneous panels
Empirical Economics, 2020 This paper develops a new method for testing for Granger non-causality in panel data models with large cross-sectional (N) and time series (T) dimensions. The method is valid in models with homogeneous or heterogeneous coefficients.
Artūras Juodis +2 more
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Perceived locus of causality and internalization: examining reasons for acting in two domains.
Journal of Personality and Social Psychology, 1989 Theories of internalization typically suggest that self-perceptions of the "causes" of (i.e. reasons for) behavior are differentiated along a continuum of autonomy that contains identifiable gradations.
Richard M. Ryan, J. Connell
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