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| Orsini, Nicola; Bellocco, Rino; Bottai, Matteo; Wolk, Alicja; Greenland, Sander. |
| Classification errors, selection bias, and uncontrolled confounders are likely to be present in most epidemiologic studies, but the uncertainty introduced by these types of biases is seldom quantified. The authors present a simple yet easy-to-use Stata command to adjust the relative risk for exposure misclassification, selection bias, and an unmeasured confounder. This command implements both deterministic and probabilistic sensitivity analysis. It allows the user to specify a variety of probability distributions for the bias parameters, which are used to simulate distributions for the bias-adjusted exposure–disease relative risk. We illustrate the command by applying it to a case–control study of occupational resin exposure and lung-cancer deaths. By... |
| Tipo: Article |
Palavras-chave: Episens; Episensi; Sensitivity analysis; Unmeasured confounder; Misclassification; Bias; Epidemiology; Research Methods/ Statistical Methods. |
| Ano: 2008 |
URL: http://purl.umn.edu/120927 |
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| Orsini, Nicola; Rizzuto, Debora; Nante, Nicola. |
| Game theory can be defined as the study of mathematical models of conflict and cooperation between intelligent and rational decision makers (Myerson 1991). Game-theory concepts apply in economy, sociology, biology, and health care, and whenever the actions of several agents (individuals, groups, or any combination of these) are interdependent. We present a new command gamet to represent the extensive form (game tree) and the strategic form (payoff matrix) of a noncooperative game and to identify the solution of a nonzero and zero-sum game through dominant and dominated strategies, iterated elimination of dominated strategies, and Nash equilibrium in pure and fully mixed strategies. Further, gamet can identify the solution of a zero-sum game through maximin... |
| Tipo: Journal Article |
Palavras-chave: Game theory; Nash equilibrium; Payoff matrix; Zero-sum game; Game tree; Research Methods/ Statistical Methods. |
| Ano: 2005 |
URL: http://purl.umn.edu/117525 |
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