unit 10 pt 1 - Unit 10: Causation Unit 10: Causation z...

Info iconThis preview shows pages 1–2. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Unit 10: Causation Unit 10: Causation z Criteria for causality » Association vs. » Causation z Different model z Different models z Different Philosophies z Hills’ Criteria Dr. A. Sanchez-Anguiano Epidemiology 6000 Introduction Introduction z Epidemiology: study of the distribution determinants and deterrents of z Epidemiology: study of the distribution, determinants and deterrents of morbidity and mortality in human populations (Oleckno, 2002) Th f f i l i t di “ ” z Therefore, one of primary goals is to discover “causes”. z Better understanding of “causes” frequently leads to more effective z Better understanding of causes frequently leads to more effective: » prevention and » control measures z Consequently to a reduction of: » incidence » prevalence or » prevalence or » severity of disease Introduction (cont Introduction (cont.) z The formulation of etiologic hypotheses most often occurs through the z The formulation of etiologic hypotheses most often occurs through the use of descriptive studies. While testing them is the primary function of the analytic study designs. z Testing an epidemiologic hypothesis involves consideration of the concept of association between a particular exposure and disease concept of association between a particular exposure and disease. z Association refers to the statistical dependence between two variables, the degree to which the rate of disease in those with specific exposure is either higher or lower than the rate of disease among those without the exposur those without the exposure Introduction (cont Introduction (cont.) Definition of HYPOTHESIS z Definition of HYPOTHESIS A Hypothesis is defined as a » “tentative explanation for – an observation, – phenomenon, or – scientific problem » that can be tested by further investigation.” (Pickett, 2000) Introduction (cont Introduction (cont.) z An association does not necessarily imply that the z An association does not necessarily imply that the observed relationship is one of cause and effect. (rooster crowing at dawn and the rising of the sun; ice cream consumption and drowning during summer These are non causa consumption and drowning during summer. These are non-causal associations). z Making judgments about causality involves a chain of logic that address two major areas: whether the association is vali and whether the totality o association is valid and whether the totality of evidence (taken from a number of sources) supports a judgment of causality . Introduction (cont Introduction (cont.) z Assessing validity (true relationships between z Assessing validity (true relationships between exposure and disease) is a matter of determining the likelihood that alternative explanations ( chance, bias likelihood that alternative explanations ( chance, bias and confounding ) could account for the findings....
View Full Document

This note was uploaded on 07/15/2011 for the course PHC 6000 taught by Professor Staff during the Summer '08 term at University of South Florida.

Page1 / 6

unit 10 pt 1 - Unit 10: Causation Unit 10: Causation z...

This preview shows document pages 1 - 2. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online