Narrow search
Showing 1 - 10 of 472
Cover Image
Causal versions of maximum entropy and principle of insufficient reason
Janzing, Dominik - In: Journal of Causal Inference 9 (2021) 1, pp. 285-301
Abstract The principle of insufficient reason (PIR) assigns equal probabilities to each alternative of a random experiment whenever there is no reason to prefer one over the other. The maximum entropy principle (MaxEnt) generalizes PIR to the case where statistical information like expectations...
Persistent link: https://www.econbiz.de/10014610914
Cover Image
Confounding and Effect Modification: Distribution and Measure
VanderWeele, Tyler J. - In: Epidemiologic Methods 1 (2012) 1, pp. 55-82
Abstract The paper considers the properties of and relations between confounding and effect modification from the … of confounding depends on how the exposure was assigned; the presence of effect modification does not. The possibility of … confounding without effect modification and vice versa is discussed both with respect to distribution and measure. Discussion is …
Persistent link: https://www.econbiz.de/10014590578
Cover Image
A Tutorial on Interaction
VanderWeele, Tyler J.; Knol, Mirjam J. - In: Epidemiologic Methods 3 (2014) 1, pp. 33-72
, different mechanistic forms of interaction, when interaction is robust to unmeasured confounding, interaction for continuous …
Persistent link: https://www.econbiz.de/10014590592
Cover Image
Doubly Robust Estimation with the R Package drgee
Zetterqvist, Johan; Sjölander, Arvid - In: Epidemiologic Methods 4 (2015) 1, pp. 69-86
Abstract A common goal of epidemiologic research is to study the association between a certain exposure and a certain outcome, while controlling for important covariates. This is often done by fitting a restricted mean model for the outcome, as in generalized linear models (GLMs) and in...
Persistent link: https://www.econbiz.de/10014590607
Cover Image
Targeted Maximum Likelihood Estimation for Dynamic and Static Longitudinal Marginal Structural Working Models
Petersen, Maya; Schwab, Joshua; Gruber, Susan; Blaser, Nello - In: Journal of Causal Inference 2 (2014) 2, pp. 147-185
Abstract This paper describes a targeted maximum likelihood estimator (TMLE) for the parameters of longitudinal static and dynamic marginal structural models. We consider a longitudinal data structure consisting of baseline covariates, time-dependent intervention nodes, intermediate...
Persistent link: https://www.econbiz.de/10014610797
Cover Image
Confounding Equivalence in Causal Inference
Pearl, Judea; Paz, Azaria - In: Journal of Causal Inference 2 (2014) 1, pp. 75-93
Abstract The paper provides a simple test for deciding, from a given causal diagram, whether two sets of variables have the same bias-reducing potential under adjustment. The test requires that one of the following two conditions holds: either (1) both sets are admissible (i.e. satisfy the...
Persistent link: https://www.econbiz.de/10014610801
Cover Image
To Adjust or Not to Adjust? Sensitivity Analysis of M -Bias and Butterfly-Bias
Ding, Peng; Miratrix, Luke W. - In: Journal of Causal Inference 3 (2015) 1, pp. 41-57
relatively small compared to confounding bias, suggesting that it is generally not a serious concern in many applied settings … -Structure tend to increase confounding bias more rapidly than M -Bias, suggesting that choosing to condition on any given …
Persistent link: https://www.econbiz.de/10014610802
Cover Image
The Deductive Approach to Causal Inference
Pearl, Judea - In: Journal of Causal Inference 2 (2014) 2, pp. 115-129
number of pending problems in causal analysis, including questions of confounding control, policy analysis, mediation …
Persistent link: https://www.econbiz.de/10014610813
Cover Image
The Entry of Randomized Assignment into the Social Sciences
Jamison, Julian C. - In: Journal of Causal Inference 7 (2019) 1
Abstract Although the concept of randomized assignment in order to control for extraneous confounding factors reaches …
Persistent link: https://www.econbiz.de/10014610866
Cover Image
Estimating Mann–Whitney-Type Causal Effects for Right-Censored Survival Outcomes
Zhang, Zhiwei; Liu, Chunling; Ma, Shujie; Zhang, Min - In: Journal of Causal Inference 7 (2019) 1
Abstract Mann–Whitney-type causal effects are clinically relevant, easy to interpret, and readily applicable to a wide range of study settings. This article considers estimation of such effects when the outcome variable is a survival time subject to right censoring. We derive and discuss...
Persistent link: https://www.econbiz.de/10014610873