Thomas Lumley Department of Statistics University of Auckland

Slides:



Advertisements
Similar presentations
Comparing different treatments How can we decide?.
Advertisements

Reporting drugs and treatments Thomas Abraham JMSC 6090.
1 Intuitive Irrationality: Reasons for Unreason. 2 Epistemology Branch of philosophy focused on how people acquire knowledge about the world Descriptive.
Risk Thomas Lumley Department of Statistics University of Auckland.
Reporting drugs and treatments Thomas Abraham. What we will learn today The difference between absolute and relative risk reduction A basic way to interpret.
Copyright ©2005 Brooks/Cole, a division of Thomson Learning, Inc. Relationships Between Categorical Variables Chapter 12.
Misconceptions and Fallacies Concerning Probability Assessments.
Extension Article by Dr Tim Kenny
© POSbase 2005 The Conjunction Fallacy Please read the following scenario: (by Tversky & Kahneman, 1983)Tversky & Kahneman, 1983 Linda is 31 years old,
Judgment in Managerial Decision Making 8e Chapter 3 Common Biases
Risk and Relative Risk. Suppose a news article claimed that drinking coffee doubled your risk of developing a certain disease. Assume the statistic was.
JEOPARDY! JEOPARDY! I Can’t Believe It’s Not JEOPARDY!
Sample Size Determination
Decision Making. Test Yourself: Decision Making and the Availability Heuristic 1) Which is a more likely cause of death in the United States: being killed.
THREE CONCEPTS ABOUT THE RELATIONSHIPS OF VARIABLES IN RESEARCH
Are exposures associated with disease?
Multiple Choice Questions for discussion
Communicating for a Knowledge Society
Health Benefits of Physical Activity
GENETIC TESTING: WHAT DOES IT REALLY TELL YOU? Lori L. Ballinger, MS, CGC Licensed Genetic Counselor University of New Mexico Cancer Center.
Fit or Unfit ? One in Four British Women Smoke Smoking is the largest cause of preventable cancer deaths in Britain.
Evaluating Information and Presenting Risk Today’s Class Fact Sheet Assignment Review Evaluating Information Presenting Risk In-class Activity This week’s.
 Get out your homework and materials for notes!  Take-home quiz due!
Anthony Calvanese Taylor Johnson J.T. Simanski. Introduction Teenagers believe that they cannot get lifestyle diseases. They think that older people like.
Thomas Lumley Department of Statistics University of Auckland
FIN 614: Financial Management Larry Schrenk, Instructor.
LESSON TWO ECONOMIC RATIONALITY Subtopic 10 – Statistical Reasoning Created by The North Carolina School of Science and Math forThe North Carolina School.
Organization of statistical research. The role of Biostatisticians Biostatisticians play essential roles in designing studies, analyzing data and.
Copyright © 2013, 2009, and 2007, Pearson Education, Inc. Chapter 10 Comparing Two Groups Section 10.1 Categorical Response: Comparing Two Proportions.
The Practice of Statistics, 5th Edition Starnes, Tabor, Yates, Moore Bedford Freeman Worth Publishers CHAPTER 4 Designing Studies 4.2Experiments.
Section 5.2 Designing Experiments AP Statistics October 27 th, 2014.
Discussing numerical data with patients. Framing Framing manipulations: describing equivalent choice situations in different ways Information on relative.
TOPIC 1.2, RISK. SPECIFICATIONS: RISK 1.18 Analyse and interpret quantitative data on illness and mortality rates to determine health risks (including.
A. Judgment Heuristics Definition: Rule of thumb; quick decision guide When are heuristics used? - When making intuitive judgments about relative likelihoods.
2 3 انواع مطالعات توصيفي (Descriptive) تحليلي (Analytic) مداخله اي (Interventional) مشاهده اي ( Observational ) كارآزمايي باليني كارآزمايي اجتماعي كارآزمايي.
Experimental Design AP Statistics Exam Review Session #4 Spring
 Get out your homework and materials for notes!  If you have your parent letter, supplies, or AP contract, please put them on my desk.
Journal Club Curriculum-Study designs. Objectives  Distinguish between the main types of research designs  Randomized control trials  Cohort studies.
Copyright © 2009 Pearson Education, Inc. Chapter 13 Experiments and Observational Studies.
20. Comparing two proportions
Communicating Risk.
AP Statistics Exam Review Topic #4
CHAPTER 4 Designing Studies
Statistics 200 Lecture #9 Tuesday, September 20, 2016
Statistics 200 Lecture #7 Tuesday, September 13, 2016
Designing Experiments
You’ve Got the Power! What African Americans Should Know About Clinical Trials National Medical Association.
Optimal Ways to learn about and communicate Evidence Based Medicine
CRITICAL NUMBERS LIVING WITH RISK
Take-home quiz due! Get out materials for notes!
Skepticism and Empiricism in Psychology
Lecture 8 – Comparing Proportions
Indiana Community Health Needs Assessment
Personal information Name: raghad alahmari age: 18 Hobby: writing.
Measures of Association
Observational Studies and Experiments
Thomas Lumley Department of Statistics University of Auckland
NAPLEX preparation: Biostatistics
Experiments and Observational Studies
Unit 6 - Comparing Two Populations or Groups
Conceptions and Misconceptions
Introducing Hypothesis Tests
remember to round it to whole numbers
Pull 3 pennies and record their average
HEURISTICS.
Intro to Epidemiology - Investigation 2-6: The Journey
Chapter 5.2 Designing Experiments
For Thursday, read Wedgwood
We should continue treating on 10 year risk
Measuring Health Disparities in Healthy People 2010
Presentation transcript:

Thomas Lumley Department of Statistics University of Auckland Risk Thomas Lumley Department of Statistics University of Auckland

Linda is 31 years old, single, outspoken, and very bright Linda is 31 years old, single, outspoken, and very bright. She majored in philosophy. As a student, she was deeply concerned with issues of discrimination and social justice, and also participated in anti-nuclear demonstrations. Which is more probable? a. Linda is a bank teller. b. Linda is a bank teller and a member of Greenpeace. Are there more English words starting with ‘e’ or with ‘e’ as the third letter? During September 2001, what was the leading preventable cause of death in the United States?

Illusions The horizontal lines are straight Your brain tries to be too clever: uses tricks that usually give more accurate results, but that fail here. Assessing probabilities has the same problem: - our brains rely on tricks that don’t always work - need to learn not to believe our gut feelings - can’t rely on the media to help us.

Kill or cure? Help to make sense of the Daily Mail’s ongoing effort to classify every inanimate object into those that cause cancer and those that prevent it.

12% is five times smaller than 17% A 12% increase is one extra case of breast cancer per 100 women A 17% decrease is five fewer cases of heart disease per 100 women 12% is five times smaller than 17% -- because the baseline risk matters

Experiments show it is easier to understand counts than probabilities What would happen to 1000 people like you? Paling Palettes: riskcomm.com

from four people in 10,000 to seven people in 10,000 Or 10,000 people like you? A 75% increase in risk: from four people in 10,000 to seven people in 10,000 Paling Palettes: riskcomm.com

Relative or absolute? We care about absolute risk differences 10 in 100 vs 11 in 100 risk of breast cancer is 1 in 100 extra risk worth drinking less? Relative risks (risk ratios) are more commonly quoted 12% increase in risk less directly useful but often more transportable from one setting to another

Up or down? Risk in group A is 11%, in group B is 10% 10/11=0.909 = 9% decrease? 11/10 = 1.10 = 10% increase? Exactly equivalent, so either is correct. Often being in one group is an action, that group usually goes on top, other group is “baseline” 10% increase from drinking vs 9% decrease from not drinking

Relative or absolute? Cholesterol-lowering drugs reduce heart attack risk about 40% Relative risk is pretty much constant across population groups Absolute risk reduction is higher for high-risk people 15 in 100 reduced by 40% is 9 in 100 3 in 100 reduced by 40% is 2 in 100 3 in 1000 reduced by 40% is 2 in 1000

1000 people take the pills. How many benefit? Relative risk is the same Actual benefit is not. Only worth treating people who have high enough risk.

More risk summaries Absolute risk reduction: risk with exposure – risk without exposure 150/1000 – 90/1000 = 60/1000 = 6% Number needed to treat: Treating 1000 people: 60 people benefit Need to treat 1000/60 = 16 people for one person to benefit Is this worthwhile? How would you decide?

Your turn Absolute risk reduction: risk with exposure – risk without exposure 3/1000 – 2/1000 = 1/1000 Number needed to treat: Treating 1000 people: 1 people benefit Need to treat 1000 people for one person to benefit

Risk summaries Relative risk = risk in exposed / risk in unexposed absolute risk reduction (or increase) = risk in exposed – risk in unexposed number needed to treat (or harm) = 1/absolute risk difference

Denial: not just a river in Egypt. Risk perception Denial: not just a river in Egypt.

Risk perception Panic vs denial Availability of examples Familiar story frame Choice to be exposed or not Feeling of control (real or not) “Natural” vs “unnatural”, “unclean” Risks to children

Rare exposures NZ Herald

Baseline risk: 1 in 70 Risk with genetic variant: 1 in 11 Relative risk ≈ 6 Risk increase = 1/11 – 1/70 = 75 per 1000 What else do we need to know? Translates to about 3/year in NZ

In this example, the genetic variant is carried by about 0 In this example, the genetic variant is carried by about 0.0011% of women Out of every 10,000 women 11 will carry the genetic variant one will get ovarian cancer sometime in her life 9989 will not carry the genetic variant 9989/70 = 143 will end up getting ovarian cancer If you could prevent cancer in the high-risk women Screen 10,000 women for the variant Find and treat 11 of them Prevent one case of ovarian cancer

Example: Physicians Health Study 22000 physicians randomly assigned to aspirin or placebo, then wait eight years Treatment Heart attack No heart attack Total aspirin 104 10933 11037 placebo 189 10845 11034 total 293 21778 22071 Risk in aspirin group = 104/11037 = 0.0094 Risk in placebo group = 189/11034 = 0.0171 Relative risk = 0.0094/0.0171 = 0.55

In words Physicians allocated to the aspirin group had a 0.55 times lower risk of heart attack than those allocated to placebo or Physicians allocated to aspirin had 45% lower risk of heart attack than those allocated to placebo other way up: 0.0171/0.0094 = 1.82 Physicians allocated to the placebo group had 1.82 times higher risk of heart attack than those allocated to aspirin

Example: Physicians Health Study 22000 physicians randomly assigned to aspirin or placebo, then wait eight years Treatment Heart attack No heart attack Total aspirin 104 10933 11037 placebo 189 10845 11034 total 293 21778 22071 Risk in aspirin group = 104/11037 = 0.0094 - Risk in placebo group = 189/11034 = 0.0171 Risk difference = 0.0094 -0.0171 = -0.0077 ≈ 8 per 1000

In words For physicians allocated to the aspirin group, the risk was reduced by 8 heart attacks per thousand. or Physicians allocated to aspirin had 0.8 percentage point lower risk of heart attack than those allocated to placebo

Summary Large relative risks make good stories but usually either a rare event or a rare exposure Convert to number of people per 1000 to get better intuition Differences in risk are easier to understand Relative risks are more likely to apply across different groups of people.

That’s all, folks.