PPT-Type I / Type II Error Control in Drug Development

Andy Grieve Head of Centre of Excellence for Statistical Innovation UCB Pharma UK PSI Annual Conference London 1417 May 2017 1 2015 2016 2002 2003 2006 2016 2007 2017 66666 2017. ANOVA can determine if there are differences among the treatments, but what is the nature of those differences?. Are the treatments measured on a continuous scale? . Look at response surfaces (linear regression, polynomials). Confirm what the data reveal: Inferential statistics. All this information is in Chapters 11 & 12 of text. For most research today, this step of the plan would use. . inferential statistics. (such as t-test and analysis of variance). . . Zvonimir . Pavlinovic. Tim King Thomas . Wies. . . New York University. An example. Rank error sources by some criterion. Report top ranked sources to the programmer. x: . int. Probability in psychology (. P = <. 0.05). The.  . p (probability).  value determines whether or not we reject the null hypothesis. We use it to estimate whether or not we think the null hypothesis is true. . Hypothesis Testing. Probability. The extent to which something is likely to happen. “On average”. Distribution of outcomes. “On Average”. Probability is based upon an infinite number of chances. Objectives . Explain . Pharmacovigilance & various types of adverse drug reactions. . List . some common adverse effects & toxicities with examples. . Discuss . drug dependence & its public health importance. . Julien Verlaguet. Software . Engineer. Facebook. A large PHP codebase (> 10M lines). Thousands of engineers. Performance matters! (. HipHop. , HHVM). The development cycle is fast: . w. e push . twice a day. CONTACTAlbert-Bttner-Strae 11WebwwwabldeTechnical support6918 DISPOSAL ADVICEFor the preservation and protection of the environment the prevention of 6817 INTELLECTUAL PROPERTY COPYRIGHTVersion ProdN Spring 2018. 1. A dice-rolling game. Two players each roll a die. The higher roll wins. Goal: roll as high as you can!. Repeat the game 6 times. 2. Hypotheses regarding . the outcome. Luck. Fraud. loaded die. Roadmap. Name analysis. Static scoping. Tree traversal, with symbol-table operations (new, insert, lookup). Today. Type checking. 2. Scanner. Parser. Tokens. Semantic Analysis. Parse Tree. AST. IR . Codegen.  = 0.05. ANOVA: Graphical. Example: ANOVA terms. Treatment 1. Treatment 2. Treatment. 3. 1. y. 11. = 48. y. 21. = 40. y. 31. = 39. 2. y. 12. = 39. y. 22. = 48. y. 32. = 30. 3. y. 13. = 42. Quantitative techniques for Economic . Analysis . II. Preetha. Rachel George. Department of Statistics. Module IV. Testing of hypothesis. Statistical test of a hypothesis is a rule or procedure which makes one to decide about the acceptance or rejection of the hypothesis.. In . statistics. , a . Type I error.  is a false positive conclusion, while a . Type II error.  is a false negative conclusion.. The probability of making a Type I error is the significance level, or alpha (α), while the probability of making a Type II error is beta (β). These risks can be minimized through careful planning in your study design.. Bonnie Halpern-Felsher, . PhD. Hypothesis Testing. Hypothesis testing is the key to our scientific inquiry. . In additional to research hypotheses, need . statistical hypotheses. .. I. nvolves . the statement of a null hypothesis, .