ISSUES THAT PLAGUE NON-INFERIORITY TRIALS PAST AND FUTURE RALPH B. D’AGOSTINO, SR. BOSTON UNIVERSITY HARVARD CLINICAL RESEARCH INSTITUTE OBJECTIVES REVIEW ISSUES: PAST, PRESENT AND FUTURE IN NON-INFERIORITY (NI) STUDIES PRESENT/ DISCUSS EXAMPLES MAKE SOME COMMENTS FOR IMPROVEMENTSBy liam
Control Files. Werner Gurtner Astronomical Institute University of Bern ILRS Workshop 3-7 October 2005 Eastbourne. Control files/mails used by ILRS. Manoeuvre predictions: Special header Standard time bias files Drag function files Time bias server EUROLAS status exchange Go-Nogo fileBy totie
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Biases. Presenter: Dr Himani Moderator: Dr P.R.Deshmukh. Framework . Introduction Terms to understand Types of bias Selection bias and types of selection bias Information bias and types of information bias How to control bias Biases specific for case control study
Biases. Presenter: Dr Himani Moderator: Dr P.R.Deshmukh. Framework. Introduction Terms to understand Types of bias Selection bias and types of selection bias Information bias and types of information bias How to control bias Biases specific for case control study
Cognitive Biases. Yan Bulgak Mar 550 December 04. What Are They. A Cognitive Bias is the result of observation by a given person or persons that creates a skewed perception of “reality”. Confirmation Bias.
Cognitive Biases . Sunil Gupta January 2011. Cognitive Bias. A cognitive bias is a pattern of poor judgment, often triggered by a particular situation. The existence of most of the particular cognitive biases listed has been verified in psychology experiments. . Why they exist.
Response biases. Think about these questions…. „I like hurting people” „ I tend to want others to admire me” „Sometimes, I am lazy.”. Response biases. Can we trust the test score? Biases related to tested person Affect the test result Threats to reliability
Cognitive Biases. How did you do on the bouncing ball count test in the video ? Do you think the directions influenced the way you interpreted the sense data? . Can you see the skull? Ready ? 1, 2, 3 Can you see the lady sitting at a makeup table?. Look at the rabbit. Look at the duck.
Heuristics and Biases. Why dumb people do smart things… and vice versa . Overview. Context Heuristics as biases (defects) Availability Anchoring and adjustment Representativeness (Revisited) Heuristics as intelligence Recognition “Fast and frugal” Tit-for-tat (social heuristics
Cognitive Biases I. Optional Reading. Today’s lecture is based primarily on: “How We Know What Isn’t So,” Chapter 1. By Thomas Gilovich , a psychologist. Patterns. Pattern Recognition. Seeing patterns in your data is a good thing, and humans are natural pattern finders.