An official website of the United States government
The odds ratio is a common measure to assess the association between abinary predictor variable and a binary outcome. In epidemiology, the outcome is often the dis- ease status, and the predictor of interest is a suspected risk factor for the disease. The purpose of the study is an attempt to establish a causal association between exposure and disease. If the object of a study is the estimation of a marginal odds ratio, defined as the ratio of the odds that would be observed in a population if everyone were exposed versus the odds in the same population if no one were exposed, methods such as the Mantel–Haenszel estimator are commonly used. When it is necessary to adjust for many confounders and/or continuous confounders, this approach results in a biased and incon- sistent estimator, including matching and stratification by the propensity score. An alter- native to matching is inverse probability weighting by the propensity score. The resulting estimator is consistent, provided the propensity score model is correct and adjusts for all confounders.
more »
« less
Understanding The Odds: Statistics in Public Health
In the world of public health and medicine, researchers are often trying to discover new ways of understanding and preventing diseases and other negative health outcomes. When public health researchers want to examine the relationship between some sort of exposure, like smoking, and a disease, such as lung cancer, they will often start by calculating what is called an odds ratio. An odds ratio is a comparison of odds between people who were exposed and people who were not exposed. However, odds ratios can be tricky to understand, even for experienced researchers. In this article, we will break down the odds ratio by reviewing the concepts and calculations of probability and odds. We will also discuss how to interpret an odds ratio, and how these ratios can be useful in real-world applications.
more »
« less
- Award ID(s):
- 2046122
- PAR ID:
- 10397174
- Date Published:
- Journal Name:
- Frontiers for Young Minds
- Volume:
- 10
- ISSN:
- 2296-6846
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
More Like this
-
-
Rational numbers (i.e., fractions, percentages, decimals, and whole-number frequencies) are notoriously difficult mathematical constructs. Yet correctly interpreting rational numbers is imperative for understanding health statistics, such as gauging the likelihood of side effects from a medication. Several pernicious biases affect health decision-making involving rational numbers. In our novel developmental framework, the natural-number bias—a tendency to misapply knowledge about natural numbers to all numbers—is the mechanism underlying other biases that shape health decision-making. Natural-number bias occurs when people automatically process natural-number magnitudes and disregard ratio magnitudes. Math-cognition researchers have identified individual differences and environmental factors underlying natural-number bias and devised ways to teach people how to avoid these biases. Although effective interventions from other areas of research can help adults evaluate numerical health information, they circumvent the core issue: people’s penchant to automatically process natural-number magnitudes and disregard ratio magnitudes. We describe the origins of natural-number bias and how researchers may harness the bias to improve rational-number understanding and ameliorate innumeracy in real-world contexts, including health. We recommend modifications to formal math education to help children learn the connections among natural and rational numbers. We also call on researchers to consider individual differences people bring to health decision-making contexts and how measures from math cognition might identify those who would benefit most from support when interpreting health statistics. Investigating innumeracy with an interdisciplinary lens could advance understanding of innumeracy in theoretically meaningful and practical ways.more » « less
-
Abstract People believe they should consider how their behavior might negatively impact other people, Yet their behavior often increases others’ health risks. This creates challenges for managing public health crises like the COVID-19 pandemic. We examined a procedure wherein people reflect on their personal criteria regarding how their behavior impacts others’ health risks. We expected structured reflection to increase people's intentions and decisions to reduce others’ health risks. Structured reflection increases attention to others’ health risks and the correspondence between people's personal criteria and behavioral intentions. In four experiments during COVID-19, people (N = 12,995) reported their personal criteria about how much specific attributes, including the impact on others’ health risks, should influence their behavior. Compared with control conditions, people who engaged in structured reflection reported greater intentions to reduce business capacity (experiment 1) and avoid large social gatherings (experiments 2 and 3). They also donated more to provide vaccines to refugees (experiment 4). These effects emerged across seven countries that varied in collectivism and COVID-19 case rates (experiments 1 and 2). Structured reflection was distinct from instructions to carefully deliberate (experiment 3). Structured reflection increased the correlation between personal criteria and behavioral intentions (experiments 1 and 3). And structured reflection increased donations more among people who scored lower in cognitive reflection compared with those who scored higher in cognitive reflection (experiment 4). These findings suggest that structured reflection can effectively increase behaviors to reduce public health risks.more » « less
-
People are involved with the collection and curation of all biodiversity data, whether they are researchers, members of the public, taxonomists, conservationists, collection managers or wildlife managers. Knowing who those people are and connecting their biographical information to the biodiversity data they collect helps us contextualise their scientific work. We are particularly concerned with those people and communities involved in the collection and identification of biological specimens. People from herbaria and natural science museums have been collecting and preserving specimens from all over the world for more than 200 years. The problem is that many of these people are only known by unstandardized names written on specimen labels, often with only initials and without any biographical information. The process of identifying and linking individuals to their biographies enables us to improve the quality of the data held by collections while also quantifying the contributions of the often underappreciated people who collected and identified these specimens. This process improves our understanding of the history of collecting, and addresses current and future needs for maintaining the provenance of specimens so as to comply with national and international practices and regulations. In this talk we will outline the steps that collection managers, data scientists, curators, software engineers, and collectors can take to work towards fully disambiguated collections. With examples, we can show how they can use these data to help them in their work, in the evaluation of their collections, and in measuring the impact of individuals and organisations, local to global.more » « less
-
Abstract Scholars and practitioners often promote direct engagement between policymakers, health workers and researchers as a strategy for overcoming barriers to utilizing scientific knowledge in health policy. However, in many settings public health officials rarely have opportunities to interact with researchers, which is a problem further exacerbated by the coronavirus disease 2019 pandemic. One prominent theory argues that policy actors will trust and utilize research findings when they perceive them to be salient, credible and legitimate. We draw on this theory to examine the conditions facilitating greater uptake of new knowledge among health officials when engagement is out of reach and they are instead exposed to new ideas through written mass communication. Using data from a survey experiment with about 260 health workers and administrators in Honduras, we find that messages from a technocratic sender based on statistical evidence improved perceptions of salience, credibility and legitimacy (SCL). Additionally, perceptions of SCL are three contextual features that operate as joint mediators between knowledge and action, and several individual characteristics also influence whether officials trust research findings enough to apply them when formulating and implementing health policies. This research can help inform the design of context-sensitive knowledge translation and exchange strategies to advance the goals of evidence-based public health, particularly in settings where direct engagement is difficult to achieve.more » « less
- Free Publicly Accessible Full Text
-
Accepted Manuscript1.0
- Journal Article:
- https://doi.org/10.3389/frym.2022.926624
