S160 #15. Comparing Two Proportions, Part 3 Odds Ratio. JC Wang. March 15, 2016
|
|
- Kerrie Morton
- 5 years ago
- Views:
Transcription
1 S60 #5 Comparing Two Proportions, Part 3 JC Wang March 5, 206
2 Outline Odds Odds 2 JC Wang WMU) S60 #5 S60, Lecture 5 2 /
3 The odds that an event occurs is Odds = Odds Probability that event occurs Probability that event does not occur = p p Probability Odds 0.0 /9 = /4 = / = / = / = 9.00 JC Wang WMU) S60 #5 S60, Lecture 5 3 /
4 iclicker Question 5. A clinical trial was conducted to study the efficacy of a new drug intended to lower the LDL low-density lipoprotein, a.k.a., bad cholesterol). All study subjects showed high LDL level at the baseline. Of the 00 treated subjects, 80 of them showed reduction to normal LDL level two weeks after treatment. What is the odds that a treated subject having reduction in LDL to normal level after two weeks? A B. 4 C. 80 D. 20 E. cannot determine JC Wang WMU) S60 #5 S60, Lecture 5 4 /
5 Outline Odds Odds 2 JC Wang WMU) S60 #5 S60, Lecture 5 5 /
6 When comparing two groups, the odds ratio is = Odds of group Odds of group 2 It is easier to interpret an OR when it s greater than and hence, when OR <, exchange the roles of the groups above to get an OR >. JC Wang WMU) S60 #5 S60, Lecture 5 6 /
7 Hepatits E Vaccine Example, revisited Hepatitis E Yes No Total Placebo Vaccine If we consider the placebo i.e., unvaccinated) group as group, then OddsHepatits Placebo) = OddsHepatits Vaccine) = = = = = = OddsHepatits Placebo) OddsHepatits Vaccine) = = 23.7 So, the odds of getting hepatitis is about 24 times greater if you remain unvaccinated. JC Wang WMU) S60 #5 S60, Lecture 5 7 /
8 Consider Disease Yes No Total Group a b a + b Group 2 c d c + d The odds ratio is then OR = a d b c = successes failures 2 failures successes 2 = successes ) /failures successes 2 /failures 2 where successes = # of successes yes s) in group and failures = # of failures no s) in group ; successes 2 = # of successes yes s) in group 2 and failures 2 = # of failures no s) in group 2. Note: assume OR >. If OR < then switch the rows above and then the new OR is the reciprocal of the old one. JC Wang WMU) S60 #5 S60, Lecture 5 8 /
9 iclicker Question 5.2 A clinical trial was conducted to study the efficacy of a new drug intended to lower the LDL low-density lipoprotein, a.k.a., bad cholesterol). All study subjects showed high LDL level at the baseline. Of the 00 treated subjects, 80 of them showed reduction to normal LDL level two weeks after treatment. On the other hand, of the 00 subjects who received placebo, only 0 showed reduction to normal LDL level after two weeks. What is the odds ratio of the treatment group versus the placebo group? A. 36 B. 4 C. 9 D. 8 E. cannot determine JC Wang WMU) S60 #5 S60, Lecture 5 9 /
10 A 95% Confidence Interval for Calculate a 95% confidence interval for the log odds ratio calculate log odds ratio [ ] ad lnor) = ln bc calculate the standard error of lnodds ratio) SE = a + b + c + d a 95% c.i. for lnor): lnor).96se, lnor) +.96SE ) 2 A 95% confidence interval for OR is e lnor).96se, e lnor)+.96se) JC Wang WMU) S60 #5 S60, Lecture 5 0 /
11 A 95% Confidence Interval for Calculate a 95% confidence interval for the log odds ratio calculate log odds ratio [ ] ad lnor) = ln bc calculate the standard error of lnodds ratio) SE = a + b + c + d a 95% c.i. for lnor): lnor).96se, lnor) +.96SE ) 2 A 95% confidence interval for OR is e lnor).96se, e lnor)+.96se) JC Wang WMU) S60 #5 S60, Lecture 5 0 /
12 A 95% Confidence Interval for Calculate a 95% confidence interval for the log odds ratio calculate log odds ratio [ ] ad lnor) = ln bc calculate the standard error of lnodds ratio) SE = a + b + c + d a 95% c.i. for lnor): lnor).96se, lnor) +.96SE ) 2 A 95% confidence interval for OR is e lnor).96se, e lnor)+.96se) JC Wang WMU) S60 #5 S60, Lecture 5 0 /
13 A 95% Confidence Interval for Calculate a 95% confidence interval for the log odds ratio calculate log odds ratio [ ] ad lnor) = ln bc calculate the standard error of lnodds ratio) SE = a + b + c + d a 95% c.i. for lnor): lnor).96se, lnor) +.96SE ) 2 A 95% confidence interval for OR is e lnor).96se, e lnor)+.96se) JC Wang WMU) S60 #5 S60, Lecture 5 0 /
14 A 95% Confidence Interval for Calculate a 95% confidence interval for the log odds ratio calculate log odds ratio [ ] ad lnor) = ln bc calculate the standard error of lnodds ratio) SE = a + b + c + d a 95% c.i. for lnor): lnor).96se, lnor) +.96SE ) 2 A 95% confidence interval for OR is e lnor).96se, e lnor)+.96se) JC Wang WMU) S60 #5 S60, Lecture 5 0 /
15 A 95% Confidence Interval for Calculate a 95% confidence interval for the log odds ratio calculate log odds ratio [ ] ad lnor) = ln bc calculate the standard error of lnodds ratio) SE = a + b + c + d a 95% c.i. for lnor): lnor).96se, lnor) +.96SE ) 2 A 95% confidence interval for OR is e lnor).96se, e lnor)+.96se) JC Wang WMU) S60 #5 S60, Lecture 5 0 /
16 Hepatits E Vaccine Example, revisited Recall that the odds ratio of placebo subjects getting hepatitis against that of vaccinated subjects is OR = = 23.7 and hence 95% c.i. for lnor): lnor) = ln23.7) = 3.65 SElnOR)) = a 95% c.i. for lnor) is given by = [ ], [ ]) = 2.004, 4.326) }{{}}{{} =.6 =.6 2 Hence, a 95% c.i. for OR is e 2.004, e 4.326) = 7.4, 75.6) So, with 95% confidence, the odds of unvaccinated subjects getting hepatitis is approximately between 7 and 76 times greater than that of vaccinated subjects. JC Wang WMU) S60 #5 S60, Lecture 5 /
17 Hepatits E Vaccine Example, revisited Recall that the odds ratio of placebo subjects getting hepatitis against that of vaccinated subjects is OR = = 23.7 and hence 95% c.i. for lnor): lnor) = ln23.7) = 3.65 SElnOR)) = a 95% c.i. for lnor) is given by = [ ], [ ]) = 2.004, 4.326) }{{}}{{} =.6 =.6 2 Hence, a 95% c.i. for OR is e 2.004, e 4.326) = 7.4, 75.6) So, with 95% confidence, the odds of unvaccinated subjects getting hepatitis is approximately between 7 and 76 times greater than that of vaccinated subjects. JC Wang WMU) S60 #5 S60, Lecture 5 /
18 Hepatits E Vaccine Example, revisited Recall that the odds ratio of placebo subjects getting hepatitis against that of vaccinated subjects is OR = = 23.7 and hence 95% c.i. for lnor): lnor) = ln23.7) = 3.65 SElnOR)) = a 95% c.i. for lnor) is given by = [ ], [ ]) = 2.004, 4.326) }{{}}{{} =.6 =.6 2 Hence, a 95% c.i. for OR is e 2.004, e 4.326) = 7.4, 75.6) So, with 95% confidence, the odds of unvaccinated subjects getting hepatitis is approximately between 7 and 76 times greater than that of vaccinated subjects. JC Wang WMU) S60 #5 S60, Lecture 5 /
19 Hepatits E Vaccine Example, revisited Recall that the odds ratio of placebo subjects getting hepatitis against that of vaccinated subjects is OR = = 23.7 and hence 95% c.i. for lnor): lnor) = ln23.7) = 3.65 SElnOR)) = a 95% c.i. for lnor) is given by = [ ], [ ]) = 2.004, 4.326) }{{}}{{} =.6 =.6 2 Hence, a 95% c.i. for OR is e 2.004, e 4.326) = 7.4, 75.6) So, with 95% confidence, the odds of unvaccinated subjects getting hepatitis is approximately between 7 and 76 times greater than that of vaccinated subjects. JC Wang WMU) S60 #5 S60, Lecture 5 /
20 Hepatits E Vaccine Example, revisited Recall that the odds ratio of placebo subjects getting hepatitis against that of vaccinated subjects is OR = = 23.7 and hence 95% c.i. for lnor): lnor) = ln23.7) = 3.65 SElnOR)) = a 95% c.i. for lnor) is given by = [ ], [ ]) = 2.004, 4.326) }{{}}{{} =.6 =.6 2 Hence, a 95% c.i. for OR is e 2.004, e 4.326) = 7.4, 75.6) So, with 95% confidence, the odds of unvaccinated subjects getting hepatitis is approximately between 7 and 76 times greater than that of vaccinated subjects. JC Wang WMU) S60 #5 S60, Lecture 5 /
21 Hepatits E Vaccine Example, revisited Recall that the odds ratio of placebo subjects getting hepatitis against that of vaccinated subjects is OR = = 23.7 and hence 95% c.i. for lnor): lnor) = ln23.7) = 3.65 SElnOR)) = a 95% c.i. for lnor) is given by = [ ], [ ]) = 2.004, 4.326) }{{}}{{} =.6 =.6 2 Hence, a 95% c.i. for OR is e 2.004, e 4.326) = 7.4, 75.6) So, with 95% confidence, the odds of unvaccinated subjects getting hepatitis is approximately between 7 and 76 times greater than that of vaccinated subjects. JC Wang WMU) S60 #5 S60, Lecture 5 /
Measuring association in contingency tables
Measuring association in contingency tables Patrick Breheny April 8 Patrick Breheny Introduction to Biostatistics (171:161) 1/25 Hypothesis tests and confidence intervals Fisher s exact test and the χ
More informationProportions, risk ratios and odds ratios
Applied Biostatistics Proportions, risk ratios and odds ratios Martin Bland Professor of Health Statistics University of York http://www-users.york.ac.uk/~mb55/ Risk difference Difference between proportions:
More informationWhat is indirect comparison?
...? series New title Statistics Supported by sanofi-aventis What is indirect comparison? Fujian Song BMed MMed PhD Reader in Research Synthesis, Faculty of Health, University of East Anglia Indirect comparison
More informationMeasuring association in contingency tables
Measuring association in contingency tables Patrick Breheny April 3 Patrick Breheny University of Iowa Introduction to Biostatistics (BIOS 4120) 1 / 28 Hypothesis tests and confidence intervals Fisher
More informationRisk Ratio and Odds Ratio
Risk Ratio and Odds Ratio Risk and Odds Risk is a probability as calculated from one outcome probability = ALL possible outcomes Odds is opposed to probability, and is calculated from one outcome Odds
More informationContingency Tables Summer 2017 Summer Institutes 187
Contingency Tables 87 Overview ) Types of Variables ) Comparing () Categorical Variables Contingency (two-way) tables Tests 3) x Tables Sampling designs Testing for association Estimation of effects Paired
More informationTo open a CMA file > Download and Save file Start CMA Open file from within CMA
Example name Effect size Analysis type Level Tamiflu Hospitalized Risk ratio Basic Basic Synopsis The US government has spent 1.4 billion dollars to stockpile Tamiflu, in anticipation of a possible flu
More informationLecture 8: Statistical Reasoning 1. Lecture 8. Confidence Intervals for Two-Population Comparison Measures
Lecture 8 Confidence Intervals for Two-Population Comparison Measures 1 Section A: Confidence Intervals for Population Comparisons: An Overview 2 2 Learning Objectives Upon completion of this lecture section,
More informationTwo-sample Categorical data: Measuring association
Two-sample Categorical data: Measuring association Patrick Breheny October 27 Patrick Breheny University of Iowa Biostatistical Methods I (BIOS 5710) 1 / 40 Introduction Study designs leading to contingency
More informationBMI 541/699 Lecture 16
BMI 541/699 Lecture 16 Where we are: 1. Introduction and Experimental Design 2. Exploratory Data Analysis 3. Probability 4. T-based methods for continous variables 5. Proportions & contingency tables -
More informationSection D. Another Non-Randomized Study Design: The Case-Control Design
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this
More informationComparing Proportions between Two Independent Populations. John McGready Johns Hopkins University
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this
More informationSupplemental Table S2: Subgroup analysis for IL-6 with BMI in 3 groups
Supplemental Table S1: Unadjusted and Adjusted Hazard Ratios for Diabetes Associated with Baseline Factors Considered in Model 3 SMART Participants Only Unadjusted Adjusted* Baseline p-value p-value Covariate
More informationReflection Questions for Math 58B
Reflection Questions for Math 58B Johanna Hardin Spring 2017 Chapter 1, Section 1 binomial probabilities 1. What is a p-value? 2. What is the difference between a one- and two-sided hypothesis? 3. What
More informationYour Diabetes Care Records
Your Diabetes Care Records Make copies of the charts in this section. These charts list important things you should discuss with your doctor at each visit. Things to Discuss with Your Health Care Team
More informationAdding Quantitative Benefit Information to DTC Promotion. Helen W. Sullivan, Ph.D., M.P.H.
DTC National Conference Washington, DC April 10-12, 2012 Adding Quantitative Benefit Information to DTC Promotion Helen W. Sullivan, Ph.D., M.P.H. Office of Prescription Drug Promotion Food and Drug Administration
More informationMaking comparisons. Previous sessions looked at how to describe a single group of subjects However, we are often interested in comparing two groups
Making comparisons Previous sessions looked at how to describe a single group of subjects However, we are often interested in comparing two groups Data can be interpreted using the following fundamental
More informationNA NA NA NA NA ,
Kansas Spotlight: Prevention This report describes prevention in three distinct categories: Access to Health Care, Immunizations (coverage), and Chronic Disease Prevention. Access Dedicated Health Care
More informationCase-control studies. Hans Wolff. Service d épidémiologie clinique Département de médecine communautaire. WHO- Postgraduate course 2007 CC studies
Case-control studies Hans Wolff Service d épidémiologie clinique Département de médecine communautaire Hans.Wolff@hcuge.ch Outline Case-control study Relation to cohort study Selection of controls Sampling
More informationNon-inferiority trials and switch from non-inferiority to superiority. D Costagliola U 943 INSERM and UPMC Paris 06
Non-inferiority trials and switch from non-inferiority to superiority D Costagliola U 943 INSERM and UPMC Paris 06 References l ICH E 9 et E10 l Points to consider on biostatistical methodological issues
More informationClinical Observation Modeling
Clinical Observation Modeling VA Informatics Architecture SOLOR Meeting Walter Sujansky January 31, 2013 Goals of Clinical Observation Modeling Create conceptual-level models of the discrete statements
More informationAgenda. Frequent Scenario WS I: Treatment Comparisons and Network Meta-Analysis: Learning the Basics
WS I: onducting & Interpreting Indirect Treatment omparisons and Network Meta-nalysis: Learning the asics onducted by members of the ISPOR Indirect Treatment omparisons Task Force Joe appelleri PhD MPH
More informationImproving Adverse Drug Reaction Information in Product Labels. EFSPI IDA Webinar 28 th Sept 2017 Sally Lettis
Improving Adverse Drug Reaction Information in Product Labels EFSPI IDA Webinar 28 th Sept 2017 Sally Lettis Improving Adverse Drug Reaction Information in Product Labels 2 Outline Current Labelling Practice
More informationConfounding in influenza VE studies in seniors, and possible solutions
Confounding in influenza VE studies in seniors, and possible solutions Michael L. Jackson Group Health Research Institute 4 th December, 2012 1 Outline Focus is on non-specific outcomes (e.g. community-acquired
More informationLearning Objectives 9/9/2013. Hypothesis Testing. Conflicts of Interest. Descriptive statistics: Numerical methods Measures of Central Tendency
Conflicts of Interest I have no conflict of interest to disclose Biostatistics Kevin M. Sowinski, Pharm.D., FCCP Last-Chance Ambulatory Care Webinar Thursday, September 5, 2013 Learning Objectives For
More information9/4/2013. Decision Errors. Hypothesis Testing. Conflicts of Interest. Descriptive statistics: Numerical methods Measures of Central Tendency
Conflicts of Interest I have no conflict of interest to disclose Biostatistics Kevin M. Sowinski, Pharm.D., FCCP Pharmacotherapy Webinar Review Course Tuesday, September 3, 2013 Descriptive statistics:
More informationIndirect Comparisons: heroism or heresy. Neil Hawkins With acknowledgements to Sarah DeWilde
Indirect Comparisons: heroism or heresy Neil Hawkins With acknowledgements to Sarah DeWilde 1 Outline Brief introduction to indirect comparisons Two practical examples Heroism or Heresy? 2 A Taxonomy of
More informationOutline. Case control studies. Study Designs. Case Control Study. Start with OUTCOME Go backwards Check for EXPOSURE. Experimental studies
Outline Case control studies Study Designs Experimental studies Observational studies Analytic studies Descriptive studies Randomized Controlled trials Case control Cohort Cross sectional Case Control
More informationExample HLA-B and abacavir. Roujeau 2014
Example HLA-B and abacavir Roujeau 2014 FDA requires testing for abacavir Treatment with abacavir is generally well tolerated, but 5% of the patients experience hypersensitivity reactions that can be life
More informationRapid appraisal of the literature: Identifying study biases
Rapid appraisal of the literature: Identifying study biases Rita Popat, PhD Clinical Assistant Professor Division of Epidemiology Stanford University School of Medicine August 7, 2007 What is critical
More informationInfluenza Vaccination Coverage in British Columbia Canadian Community Health Survey 2011 & 2012
Background The Canadian Community Health Survey (CCHS) is a cross-sectional survey that collects information related to the health status, health care utilization and health determinants of the Canadian
More informationSupplementary Online Content
Supplementary Online Content Zhu AX, Kudo M, Assenat E, et al. Effect of everolimus on survival in advanced hepatocellular carcinoma after failure of sorafenib: the EVOLVE-1 randomized clinical trial.
More informationComparing Proportions between Two Independent Populations. John McGready Johns Hopkins University
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike License. Your use of this material constitutes acceptance of that license and the conditions of use of materials on this
More informationObservational Medical Studies. HRP 261 1/13/ am
Observational Medical Studies HRP 261 1/13/03 10-11 11 am To Drink or Not to Drink? Volume 348:163-164 January 9, 2003 Ira J. Goldberg, M.D. A number of epidemiologic studies have found an association
More informationLow HDL and Diabetic Dyslipidemia
The Lowdown: Low HDL and Diabetic Dyslipidemia Patients with diabetes commonly have a low-density lipoprotein cholesterol (LDL-C) no higher than that of the general population. What treatment is warranted
More informationEpidemiology. Bis vivit qui bene vivit
Epidemiology Bis vivit qui bene vivit What is Epidemiology? Epidemiology, literally translated from Greek, means "the study of [a] people". http://www.aea.asn.au/home_whatisepidemiology.htm Epidemiology
More information17/10/2012. Could a persistent cough be whooping cough? Epidemiology and Statistics Module Lecture 3. Sandra Eldridge
Could a persistent be whooping? Epidemiology and Statistics Module Lecture 3 Sandra Eldridge Aims of lecture To explain how to interpret a confidence interval To explain the different ways of comparing
More informationChapter 15: Continuation of probability rules
Chapter 15: Continuation of probability rules Example: HIV-infected women attending either an infectious disease clinic in Bangkok were screened for high-risk HPV and received a Pap test; those with abnormal
More informationAn example of a systematic review and meta-analysis
An example of a systematic review and meta-analysis Sattar N et al. Statins and risk of incident diabetes: a collaborative meta-analysis of randomised statin trials. Lancet 2010; 375: 735-742. Search strategy
More informationFREC 408 Probability When Using Contingency Tables
B 5XOHVVRIDU 3UREDELOLW\RI $8QLRQ A = A) + A &RQGLWLRQDO 3UREDELOLW\ A = A 3UREDELOLW\RI DQ,QWHUVHFWLRQ P ( A = A This is the experiment The following is some data from an experiment in smoking succession.
More informationSummary of two retracted Mawson papers comparing health outcomes in vaccinated vs unvaccinated children from a survey of homeschooled children
Summary of two retracted Mawson papers comparing health outcomes in vaccinated vs unvaccinated children from a survey of homeschooled children By Melissa Smith and Rob Verkerk PhD, Science Unit, Alliance
More informationSupplementary Appendix
Supplementary Appendix This appendix has been provided by the authors to give readers additional information about their work. Supplement to: Serra AL, Poster D, Kistler AD, et al. Sirolimus and kidney
More informationBinary Diagnostic Tests Paired Samples
Chapter 536 Binary Diagnostic Tests Paired Samples Introduction An important task in diagnostic medicine is to measure the accuracy of two diagnostic tests. This can be done by comparing summary measures
More informationTitle: Statins for haemodialysis patients with diabetes? Long-term follow-up endorses the original conclusions of the 4D study.
Manuscript type: Invited Commentary: Title: Statins for haemodialysis patients with diabetes? Long-term follow-up endorses the original conclusions of the 4D study. Authors: David C Wheeler 1 and Bertram
More informationIs it ever too late for cardiovascular prevention and rehabilitation? Prof. Dr. Helmut Gohlke Herz-Zentrum Bad Krozingen, Germany
Is it ever too late for cardiovascular prevention and rehabilitation? Prof. Dr. Helmut Gohlke Herz-Zentrum Bad Krozingen, Germany The demographic issue Life expectancy is increasing Patients are getting
More informationILLUMINATE. Effects of torcetrapib in patients at high risk for coronary events NEJM. 2007; 357:
ILLUMINATE. Effects of torcetrapib in patients at high risk for coronary events NEJM. 2007; 357: 2109-2122. ILLUMINATE The most important trial since 2000? Background Inhibition of cholesteryl ester transfer
More informationData and Approaches in National and International Immunization Studies. Emory University, Schools of Public Health & Medicine & CHRSE
Data and Approaches in National and International Immunization Studies Saad B. Omer, MBBS MPH PhD Emory University, Schools of Public Health & Medicine & CHRSE Outline Characteristics of vaccine refusers
More informationUpdates in Therapeutics 2015: The Pharmacotherapy Preparatory Review & Recertification Course
Updates in Therapeutics 2015: The Pharmacotherapy Preparatory Review & Recertification Course Study Designs: Fundamentals and Interpretation Kevin M. Sowinski, Pharm.D., FCCP Purdue University, College
More informationEpidemiologic study designs
Epidemiologic study designs and critical appraisal of scientific papers Rolf H.H. Groenwold, MD, PhD Bio sketch MD, PhD in epidemiology Associate professor of Epidemiology at UMC Utrecht Research focus
More informationNo Large Differences Among Centers in a Multi-Center Neurosurgical Clinical Trial
No Large Differences Among Centers in a Multi-Center Neurosurgical Clinical Trial Emine O Bayman 1,2, K Chaloner 2,3, BJ Hindman 1 and MM Todd 1 1:Anesthesia, 2:Biostatistics, 3: Stat and Actuarial Sc,
More informationIs There An Association?
Is There An Association? Exposure (Risk Factor) Outcome Exposures Risk factors Preventive measures Management strategy Independent variables Outcomes Dependent variable Disease occurrence Lack of exercise
More informationReview Statistics review 11: Assessing risk Viv Bewick 1, Liz Cheek 1 and Jonathan Ball 2
Available online http://ccforum.com/content/8/4/87 Review Statistics review 11: Assessing risk Viv Bewick 1, Liz Cheek 1 and Jonathan Ball 1 Senior Lecturer, School of Computing, Mathematical and Information
More informationBIOB111_CHBIO - Tutorial activity for Session 12
BIOB111_CHBIO - Tutorial activity for Session 12 General topic for week 6 Session 12 Lipids Useful Links: 1. Animations on Cholesterol (its synthesis, lifestyle factors, LDL) http://www.wiley.com/college/boyer/0470003790/animations/cholesterol/cholesterol.htm
More informationNote: During any ONE run the ph remains constant. It may be at any one of the above levels but it never change during a single run.
1 BGYC34 (2007) PhysioEx Lab 10 AcidBase Balance Marking Scheme Part 1 Complete PhysioEx lab #10. Handin all of the pages associated with the lab. Note that there are 9 activities to be completed. You
More informationAn analysis of several novel frameworks and models in the consensus reaching process. Hengjie Zhang
An analysis of several novel frameworks and models in the consensus reaching process Hengjie Zhang Outline Background: consensus reaching process Model I: consensus with minimum adjustments Model II: consensus
More informationHerd Protection- Efficacy vs effectiveness The Importance of Cluster-Randomized Trials to assess Vaccine Herd Protection
Herd Protection- Efficacy vs effectiveness The Importance of Cluster-Randomized Trials to assess Vaccine Herd Protection Anna Lena Lopez, MD, MPH University of the Philippines Manila- National Institutes
More informationEfficient analysis of ordinal functional outcome scales
Efficient analysis of ordinal functional outcome scales Gordon D Murray University of Edinburgh Outline of presentation Functional outcome scales Ordinal analysis Case study: SCAST Results Points to consider
More informationIs it worth offering cardiovascular disease prevention to the elderly? Prof. Dr. Helmut Gohlke Herz-Zentrum Bad Krozingen, Germany
Is it worth offering cardiovascular disease prevention to the elderly? Prof. Dr. Helmut Gohlke Herz-Zentrum Bad Krozingen, Germany Is it worth offering cardiovascular disease prevention to the elderly?
More informationFacts on Fats. Ronald P. Mensink
Facts on Fats Ronald P. Mensink Department of Human Biology NUTRIM, School for Nutrition, Toxicology and Metabolism Maastricht University Maastricht The Netherlands Outline of the Presentation Saturated
More informationUse of Subgroups to Rescue a Trial or Improve Benefit-Risk
1 Use of Subgroups to Rescue a Trial or Improve Benefit-Risk Martin King, Ph.D. Director, Statistics Global Pharmaceutical R&D, Abbott Abbott Park, IL USA 2 Disclaimer The opinions in this presentation
More informationSupplementary Table 1. The distribution of IFNL rs and rs and Hardy-Weinberg equilibrium Genotype Observed Expected X 2 P-value* CHC
Supplementary Table 1. The distribution of IFNL rs12979860 and rs8099917 and Hardy-Weinberg equilibrium Genotype Observed Expected X 2 P-value* CHC rs12979860 (n=3129) CC 1127 1145.8 CT 1533 1495.3 TT
More informationSupplementary Online Content
Supplementary Online Content Clair C, Rigotti NA, Porneala B, et al. Association of smoking cessation and weight change with cardiovascular disease among people with and without diabetes. JAMA. doi:10.1001/jama.2013.1644.
More informationWhy Mixed Effects Models?
Why Mixed Effects Models? Mixed Effects Models Recap/Intro Three issues with ANOVA Multiple random effects Categorical data Focus on fixed effects What mixed effects models do Random slopes Link functions
More informationChapter 13 Estimating the Modified Odds Ratio
Chapter 13 Estimating the Modified Odds Ratio Modified odds ratio vis-à-vis modified mean difference To a large extent, this chapter replicates the content of Chapter 10 (Estimating the modified mean difference),
More informationSummary of Key Points WHO Position Paper on BCG Vaccine, February 2018
Summary of Key Points WHO Position Paper on BCG Vaccine, February 2018 1 Introduction This position paper replaces the 2004 WHO position paper on Bacille Calmette-Guérin (BCG) vaccine and the 2007 WHO
More informationCoach on Call. Please give me a call if you have more questions about this or other topics.
Coach on Call It was great to talk with you. Thank you for your interest in. I hope you find this tip sheet helpful. Please give me a call if you have more questions about this or other topics. As your
More information2013 ACC AHA LIPID GUIDELINE JAY S. FONTE, MD
2013 ACC AHA LIPID GUIDELINE JAY S. FONTE, MD How do you interpret my blood test results? What are our targets for these tests? Before the ACC/AHA Lipid Guidelines A1c:
More informationSystematic review of the non- specific effects of BCG, DTP and measles containing vaccines
Systematic review of the non- specific effects of BCG, DTP and measles containing vaccines Higgins JPT, Soares- Weiser K, Reingold A 13 March 2014 Contents 1 Executive Summary... 3 2 Background... 4 3
More informationCan Animals Experience Emotions? Model Diagnostics Demographic variable Companion Animal. Deviance
1 2 3 Table 1: Table showing significant demographic influences on responses to the question can animals experience the following emotions? Significance of odds ratios: * p
More informationMeasuring Real-World Outcomes. Brendan Barrett
Measuring Real-World Outcomes Brendan Barrett What is An Outcome? Potential target of an intervention Potential result of an exposure A future or current event or state Can be good or bad e.g. cure versus
More informationThe JUPITER trial: What does it tell us? Alice Y.Y. Cheng, MD, FRCPC January 24, 2009
The JUPITER trial: What does it tell us? Alice Y.Y. Cheng, MD, FRCPC January 24, 2009 Learning Objectives 1. Understand the role of statin therapy in the primary and secondary prevention of stroke 2. Explain
More informationAssessing Vaccine Safety Post Licensure. Neal A. Halsey Johns Hopkins University
Assessing Vaccine Safety Post Licensure Neal A. Halsey Johns Hopkins University Inactivated Respiratory Syncytial Virus Vaccine: 1960 s Formalin inactivated Administered to infants Minimal reactions Induced
More informationIntroducing Cholesterol Regulation Complex*!
New Shaklee Product Introducing Cholesterol Regulation Complex*! #20648 *This statement has not been evaluated by the Food and Drug Administration. This product is not intended to diagnose, treat, cure,
More informationModifying effects of dietary polyunsaturated fatty acid (PUFA) on levels of cholesterol and their implications for heart health
Modifying effects of dietary polyunsaturated fatty acid (PUFA) on levels of cholesterol and their implications for heart health Robert Clarke Clinical Trial Service Unit University of Oxford 28 th May
More informationLipoproteins Metabolism
Lipoproteins Metabolism LEARNING OBJECTIVES By the end of this Lecture, the student should be able to describe: What are Lipoproteins? Describe Lipoprotein Particles. Composition of Lipoproteins. The chemical
More informationInhibition of PCSK9: The Birth of a New Therapy
Inhibition of PCSK9: The Birth of a New Therapy Prof. John J.P. Kastelein, MD PhD FESC Dept. of Vascular Medicine Academic Medical Center / University of Amsterdam The Netherlands Disclosures Dr. Kastelein
More informationWelcome to this series focused on sources of bias in epidemiologic studies. In this first module, I will provide a general overview of bias.
Welcome to this series focused on sources of bias in epidemiologic studies. In this first module, I will provide a general overview of bias. In the second module, we will focus on selection bias and in
More informationCholesterol targets and therapy Thomas C. Andrews, MD, FACC
Cholesterol targets and therapy Thomas C. Andrews, MD, FACC 2 Statins in secondary prevention Still first line therapy! First line therapy: high intensity statin Dose individualized based on baseline LDL
More informationConfounding Bias: Stratification
OUTLINE: Confounding- cont. Generalizability Reproducibility Effect modification Confounding Bias: Stratification Example 1: Association between place of residence & Chronic bronchitis Residence Chronic
More informationBinary Diagnostic Tests Two Independent Samples
Chapter 537 Binary Diagnostic Tests Two Independent Samples Introduction An important task in diagnostic medicine is to measure the accuracy of two diagnostic tests. This can be done by comparing summary
More informationTypes of data and how they can be analysed
1. Types of data British Standards Institution Study Day Types of data and how they can be analysed Martin Bland Prof. of Health Statistics University of York http://martinbland.co.uk In this lecture we
More information7 ANIMALS Blood Vessels.notebook. January 11, Human Blood Vessels
Human Blood Vessels 1 Arteries All arteries take blood AWAY from the heart, and most arteries carry oxygenated blood. The one exception is the PULMONARY ARTERY which carries de oxygenated blood to the
More informationCreating Healthier Lives. Cholesterol Reduction Complex Lower Your Cholesterol Naturally
Cholesterol Reduction Complex Lower Your Cholesterol Naturally 1 DID YOU KNOW? About 40% of Canadian adults have high cholesterol. 2 DID YOU KNOW? YOU ARE AT RISK FOR HIGH CHOLESTEROL If you have a poor
More informationTo educate and empower women about total wellness through Information & the opportunity for interaction.
To educate and empower women about total wellness through Information & the opportunity for interaction. INTRODUCING THE BOARD Sharon Baker Amy Astin Sonya Briscoe Susan Culberson Louise Michelson JoAnne
More informationFOURIER STUDY GREYLOCK PRESS: CTS PRODUCT SAMPLE - FOURIER YES. Did the study achieve its main objective?
FOURIER STUDY Did the study achieve its main objective? 2 15% 1 5% 9.8% YES FOURIER compared Repatha with placebo in patients who were taking a statin and had hardening or narrowing of the arteries and
More informationAnalytic Methods for Infectious Disease Lecture 3
Analytic Methods for Infectious Disease Lecture 3 M. Elizabeth Halloran Hutchinson Research Center and University of Washington Seattle, WA, USA January 13, 2009 Herd Immunity Definition Manifestations
More informationState of the art pharmacoepidemiological study designs for post-approval risk assessment
State of the art pharmacoepidemiological study designs for post-approval risk assessment Cardiac Safety Research Consortium Think Tank Round Table Meeting Thursday, March 6, 2014 Jennifer L. Lund, PhD
More informationNetwork Meta-Analysis for Comparative Effectiveness Research
Network Meta-Analysis for Comparative Effectiveness Research Joseph C. Cappelleri, Ph.D., M.P.H. Pfizer Inc Groton, CT e-mail:joseph.c.cappelleri@pfizer.com Oral presentation at the 19 th Annual Biopharmaceutical
More information5. Cardiovascular Disease & Stroke
5. Cardiovascular Disease & Stroke 64: Self-Reported Heart Disease 66: Heart Disease Management 68: Heart Disease Mortality 70: Heart Disease Mortality Across Life Span 72: Stroke Mortality 185: Map 3:
More informationWelcome to this third module in a three-part series focused on epidemiologic measures of association and impact.
Welcome to this third module in a three-part series focused on epidemiologic measures of association and impact. 1 This three-part series focuses on the estimation of the association between exposures
More informationCapture-recapture method for assessing publication bias
Received: 30.9.2009 Accepted: 19.1.2010 Original Article Capture-recapture method for assessing publication bias Jalal Poorolajal* a, Ali Akbar Haghdoost b, Mahmood Mahmoodi a, Reza Majdzadeh a, Siavosh
More informationSupplementary materials: Predictors of response to pegylated interferon in chronic hepatitis B: a
Supplementary materials: Predictors of response to pegylated interferon in chronic hepatitis B: a real-world hospital-based analysis Yin-Chen Wang 1, Sien-Sing Yang 2*, Chien-Wei Su 1, Yuan-Jen Wang 3,
More informationThe role of Randomized Controlled Trials
The role of Randomized Controlled Trials Dr. Georgia Salanti Lecturer in Epidemiology University of Ioannina School of Medicine Outline Understanding study designs and the role of confounding Observational
More informationAspirine pour tous les patients à haut risque?
Aspirine pour tous les patients à haut risque? Gilles Lemesle, Centre Hémodynamique, CHRU de Lille Cliquez pour modifier le style des sous titres du masque The clinical point of view Ratio Ischaemic events
More informationEMCDDA DOCUMENTS ON IMPROVING COMPARABILITY - DRUG-RELATED INFECTIOUS DISEASES
EMCDDA DOCUMENTS ON IMPROVING COMPARABILITY - DRUG-RELATED INFECTIOUS DISEASES 1. Draft guidelines key indicator infections 2. Infection Indicator Map 3. Standard table 09-INFECTIONS-2000 EMCDDA / 2000
More information2016 Stroke Statistics
2016 Stroke Statistics Carotid Artery Procedure Mortality Rate *The Joint Commission Requirement < 6 % LUMC 3.0% *The Joint Commission Requirement < 3 % LUMC 0.0% Rate of stroke or death within 30 days
More informationSupplementary Online Content
Supplementary Online Content Lotta LA, Stewart ID, Sharp SJ, et al. Association of genetically enhanced lipoprotein lipase mediated lipolysis and low-density lipoprotein cholesterol lowering alleles with
More informationMeta-Analysis De-Mystified: A Step-by-Step Workshop
Meta-Analysis De-Mystified: A Step-by-Step Workshop Eval Café Evaluation Center at WMU January, 2012 Robert McCowen, IDPE robert.h.mccowen@wmich.edu Overview Background and Context Applications of Meta-Analysis
More informationEpidemiological study design. Paul Pharoah Department of Public Health and Primary Care
Epidemiological study design Paul Pharoah Department of Public Health and Primary Care Molecules What/why? Organelles Cells Tissues Organs Clinical medicine Individuals Public health medicine Populations
More information