Causal inference Afshin Ostovar Bushehr University of Medical Sciences Bushehr, 2012 10/4/20151.

Slides:



Advertisements
Similar presentations
Causation When do we have enough evidence? Sam Bracebridge.
Advertisements

Causation Jay M. Fleisher.
Deriving Biological Inferences From Epidemiologic Studies.
Causality Causality Hill’s Criteria Cross sectional studies.
Causality Inferences. Objectives: 1. To understand the concept of risk factors and outcome in a scientific way. 2. To understand and comprehend each and.
Bradford Hill’s Criteria for Inferring Causality
1 Case-Control Study Design Two groups are selected, one of people with the disease (cases), and the other of people with the same general characteristics.
Causal Inference in Epidemiology
The burden of proof Causality FETP India. Competency to be gained from this lecture Understand and use Doll and Hill causality criteria.
Epidemiology Kept Simple
Microbiology Koch and establishing causal links between microrganisms and disease.
1.40 p= Epidemiologic Association Chance Bias Confounding Truth.
THE PROCESS OF SCIENCE. Assumptions  Nature is real, understandable, knowable through observation  Nature is orderly and uniform  Measurements yield.
Epidemiology & Critical Thinking D. Morse st Avenue Tel: Office Hours: 4:00-5:00 (M & W)
Evaluating environmental/occupational “clusters” of disease Robert J. McCunney, MD.
Association to Causation. Sequence of Studies Clinical observations Available data Case-control studies Cohort studies Randomized trials.
Scientific method - 1 Scientific method is a body of techniques for investigating phenomena and acquiring new knowledge, as well as for correcting and.
Causation Abdulaziz Bin Saeed Assistant professor Fam&Com Medicine.
STATISTICAL ASSOCIATION AND CAUSALITY Nigel Paneth.
Showing Cause, Introduction to Study Design Principles of Epidemiology Lecture 4 Dona Schneider, PhD, MPH, FACE.
Cause or merely association?
Scientific Method and Experimentation
GerstmanGerstmanChapter 21GerstmanChapter 21 Epidemiology Chapter 2 Causal Concepts.
Dr. Zahid Ahmad Butt. Cause “An antecedent event, condition, or characteristic that was necessary for the occurrence of the disease at the moment it occurred,
1 Causation in Epidemiological Studies Dr. Birgit Greiner Senior Lecturer.
Causation and the Rules of Inference Classes 4 and 5.
Evidence-Based Medicine 3 More Knowledge and Skills for Critical Reading Karen E. Schetzina, MD, MPH.
Web of Causation; Exposure and Disease Outcomes Thomas Songer, PhD Basic Epidemiology South Asian Cardiovascular Research Methodology Workshop.
 Is there a comparison? ◦ Are the groups really comparable?  Are the differences being reported real? ◦ Are they worth reporting? ◦ How much confidence.
Mother and Child Health: Research Methods G.J.Ebrahim Editor Journal of Tropical Pediatrics, Oxford University Press.
Lung Cancer Molecular Pathology of Cancer Boot Camp January 4, 2012 Jennifer Rider, ScD.
Causation. Associations may be due to Chance (random error) statistics are used to reduce it by appropriate design of the study statistics are used to.
Field Epidemiology Fall 2000 Patty Kissinger, PhD John L. Clayton, MPH Megan O’Brien, MPH.
CAUSAL INFERENCE Presented by: Dan Dowhower Alysia Cohen H 615 Friday, October 4, 2013.
Is the association causal, or are there alternative explanations? Epidemiology matters: a new introduction to methodological foundations Chapter 8.
A short introduction to epidemiology Chapter 10: Interpretation Neil Pearce Centre for Public Health Research Massey University, Wellington, New Zealand.
Study Designs for Clinical and Epidemiological Research Carla J. Alvarado, MS, CIC University of Wisconsin-Madison (608)
Biological Science.
Causation.
Research Methods in Health Psychology Chapter 2. Science Science is not a thing in and of itself. It is a set of methods used to understand natural phenomena.
Causal relationships, bias, and research designs Professor Anthony DiGirolamo.
Unit 3: Credibility of Health Claims. Credibility of health claims How do you know what to believe? What makes information reliable? Can you really lose.
Unit 2 – Public Health Epidemiology Chapter 4 – Epidemiology: The Basic Science of Public Health.
Instructor Resource Chapter 11 Copyright © Scott B. Patten, Permission granted for classroom use with Epidemiology for Canadian Students: Principles,
Instructor Resource Chapter 18 Copyright © Scott B. Patten, Permission granted for classroom use with Epidemiology for Canadian Students: Principles,
Causation and association Dr. Salwa Tayel Family and Community Medicine Department King Saud University.
Reading Health Research Critically The first four guides for reading a clinical journal apply to any article, consider: the title the author the summary.
SCIENCE The aim of this tutorial is to help you learn to identify and evaluate scientific methods and assumptions.
Probability & Significance Everything you always wanted to know about p-values* *but were afraid to ask Evidence Based Chiropractic April 10, 2003.
QUESTIONS TO ASK WHEN EXAMINING ALTERNATIVE OPINION? How to evaluate an argument calmly and objectively Avoid being swayed by a presenter’s delivery techniques.
Showing Cause, Introduction to Study Design Principles of Epidemiology.
Chapter 2: General Concepts Chapter 2 Causal Concepts
“ WHAT Science IS AND Science is NOT ” SCIENCE IS…
INFERENSI KAUSAL. 12/30/2001Data analysis and causal inference 2 Causal relations and public health Many public health questions hinge on causal relations,
Ch Epidemiology Microbiology.
Chapter 9 Causality.
Writing a sound proposal
© 2010 Jones and Bartlett Publishers, LLC
Interpreting numbers – more tricky bits
Causation Analysis in Occupational and Environmental Medicine
Showing Cause, Introduction to Study Design
Association & Causation in epidemiological studies
SUSSER’S CAUSAL CRITERIA
Chapter 4: Inductive Arguments
How can we identify a novel carcinogen?
Causality assessment Theoretical background
Causation Learning Objectives
Critical Appraisal วิจารณญาณ
Relationship Relation: Association: real and spurious Statistical:
Presentation transcript:

Causal inference Afshin Ostovar Bushehr University of Medical Sciences Bushehr, /4/20151

“The world is richer in associations than meanings, and it is the part of wisdom to differentiate the two.” John Barth, novelist. 10/4/20152

“Who knows, asked Robert Browning, but the world may end tonight? True, but on available evidence most of us make ready to commute on the 8.30 next day.” A. B. Hill 10/4/20153

The concept of causality Moving a light switch causes the light to turn on 10/4/20154

What’s the cause? The mother who replaced the burned-out light bulb The electrician who has just replaced a defective circuit breaker The lineman who repaired the transformer The social service agency that arranged to pay the electricity bill The power company, the political authority, … 10/4/20155

Mervyn Susser proposes that for epidemiologists a causal relation has the following attributes: Association Time order Direction 10/4/20156

A cause is something that is associated with its effect, is present before or at least at the same time as its effect, and acts on its effect. In principle, a cause can be necessary – without it the effect will not occur – and/or sufficient – with it the effect will result regardless of the presence or absence of other factors. 10/4/20157

Sufficient Component Cause Model 10/4/20158

Sufficient Component Cause Model 10/4/20159

Causal Inference Direct observation vs. inference: Much scientific knowledge is gained through direct observation. Even observation involves inference. 10/4/201510

Causal Inference Difficulties that arise from latency and induction: The two-week induction period of measles and its infectiousness before the appearance of symptoms Confounding the seasonality by food availability for Pellagra. Low rates of lung cancer in populations with high smoking rates (neglecting the long induction interval) 10/4/201511

Idealized view of the scientific process Positing of conceptual models (conceptual hypotheses); Deduction of specific, operational hypotheses; and Testing of operational hypotheses. 10/4/201512

The cycle of scientific progress 10/4/201513

Influence of knowledge and paradigms The Henle-Koch Postulates (1884):  The parasite (the original term) must be present in all who have the disease;  The parasite can never occur in healthy persons;  The parasite can be isolated, cultured and capable of passing the disease to others. 10/4/201514

Influence of knowledge and paradigms Rivers, 1937; Evans 1978:  Disease production may require co-factors.  Viruses cannot be cultured like bacteria because viruses need living cells in which to grow.  Pathogenic viruses can be present without clinical disease (subclinical infections, carrier states). 10/4/201515

Criteria for causal inference in epidemiology The basic underlying questions are: 1. Is the association real or artefactual? 2. Is the association secondary to a "real" cause? 10/4/201516

The Bradford Hill criteria 1. Strength of the association  The stronger an association, the less it could merely reflect the influence of some other etiologic factor(s).  This criterion includes consideration of the statistical precision (minimal influence of chance) and methodologic rigor of the existing studies with respect to bias (selection, information, and confounding). 10/4/201517

The Bradford Hill criteria How strong is "strong"? A rule-of-thumb: 10/4/201518

The Bradford Hill criteria 2. Consistency  Replication of the findings by different investigators, at different times, in different places, with different methods and the ability to convincingly explain different results. 10/4/201519

The Bradford Hill criteria 3. Specificity of the association  There is an inherent relationship between specificity and strength in the sense that the more accurately defined the disease and exposure, the stronger the observed relationship should be.  The fact that one agent contributes to multiple diseases is not evidence against its role in any one disease. 10/4/201520

The Bradford Hill criteria 4. Temporality  The ability to establish that the putative cause in fact preceded in time the presumed effect. 10/4/201521

The Bradford Hill criteria 5. Biological gradient  Incremental change in disease rates in conjunction with corresponding changes in exposure.  The verification of a dose-response relationship consistent with the hypothesized conceptual model. 10/4/201522

The Bradford Hill criteria 6. Plausibility  We are much readier to accept the case for a relationship that is consistent with our general knowledge and beliefs.  Obviously this tendency has pitfalls, but commonsense often serves us. 10/4/201523

The Bradford Hill criteria 7. Coherence  How well do all the observations fit with the hypothesized model to form a coherent picture? 10/4/201524

The Bradford Hill criteria 8. Experiment  The demonstration that under controlled conditions changing the exposure causes a change in the outcome is of great value, some would say indispensable, for inferring causality. 10/4/201525

The Bradford Hill criteria 9. Analogy  We are readier to accept arguments that resemble others we accept. 10/4/201526