digplanet beta 1: Athena
Share digplanet:

Agriculture

Applied sciences

Arts

Belief

Chronology

Culture

Education

Environment

Geography

Health

History

Humanities

Language

Law

Life

Mathematics

Nature

People

Politics

Science

Society

Technology

In statistics, a confounding variable (also confounding factor, hidden variable, lurking variable, a confound, or confounder) is an extraneous variable in a statistical model that correlates (positively or negatively) with both the dependent variable and the independent variable. A perceived relationship between an independent variable and a dependent variable that has been misestimated due to the failure to account for a confounding factor is termed a spurious relationship, and the presence of misestimation for this reason is termed omitted-variable bias. In the case of risk assessments evaluating the magnitude and nature of risk to human health, it is important to control for confounding to isolate the effect of a particular hazard such as a food additive, pesticide, or new drug. For prospective studies, it is difficult to recruit and screen for volunteers with the same background (age, diet, education, geography, etc.), and in historical studies, there can be similar variability. Due to the inability to control for variability of volunteers and human studies, confounding is a particular challenge. For these reasons, experiments offer a way to avoid most forms of confounding.

As an example, suppose that there is a statistical relationship between ice-cream consumption and number of drowning deaths for a given period. These two variables have a positive correlation with each other. An evaluator might attempt to explain this correlation by inferring a causal relationship between the two variables (either that ice-cream causes drowning, or that drowning causes ice-cream consumption). However, a more likely explanation is that the relationship between ice-cream consumption and drowning is spurious and that a third, confounding, variable (the season) influences both variables: during the summer, warmer temperatures lead to increased ice-cream consumption as well as more people swimming and thus more drowning deaths.

## Types of confounding

In some disciplines, confounding is categorized into different types. In epidemiology, one type is "confounding by indication",[1] which relates to confounding from observational studies. Because prognostic factors may influence treatment decisions (and bias estimates of treatment effects), controlling for known prognostic factors may reduce this problem, but it is always possible that a forgotten or unknown factor was not included or that factors interact complexly. Confounding by indication has been described as the most important limitation of observational studies. Randomized trials are not affected by confounding by indication due to random assignment.

Confounding variables may also be categorised according to their source. The choice of measurement instrument (operational confound), situational characteristics (procedural confound), or inter-individual differences (person confound).

• An operational confound can occur in both experimental and non-experimental research designs. This type of confound occurs when a measure designed to assess a particular construct inadvertently measures something else as well.[2]
• A procedural confound can occur in a laboratory experiment or a quasi-experiment. This type of confound occurs when the researcher mistakenly allows another variable to change along with the manipulated independent variable.[2]
• A person confound occurs when two or more groups of units are analyzed together (e.g., workers from different occupations), despite varying according to one or more other (observed or unobserved) characteristics (e.g., gender).[3]

## Examples

In risk assessments, factors such as age, gender, and educational levels often have impact on health status and so should be controlled. Beyond these factors, researchers may not consider or have access to data on other causal factors. An example is on the study of smoking tobacco on human health. Smoking, drinking alcohol, and diet are lifestyle activities that are related. A risk assessment that looks at the effects of smoking but does not control for alcohol consumption or diet may overestimate the risk of smoking.[4] Smoking and confounding are reviewed in occupational risk assessments such as the safety of coal mining.[5] When there is not a large sample population of non-smokers or non-drinkers in a particular occupation, the risk assessment may be biased towards finding a negative effect on health.

## Decreasing the potential for confounding to occur

A reduction in the potential for the occurrence and effect of confounding factors can be obtained by increasing the types and numbers of comparisons performed in an analysis.[citation needed] If a relationship holds among different subgroups of analyzed units, confounding may be less likely. That said, if measures or manipulations of core constructs are confounded (i.e., operational or procedural confounds exist), subgroup analysis may not reveal problems in the analysis. Additionally, increasing the number of comparisons can create other problems (see multiple comparisons).

Peer review is a process that can assist in reducing instances of confounding, either before study implementation or after analysis has occurred. Peer review relies on collective expertise within a discipline to identify potential weaknesses in study design and analysis, including ways in which results may depend on confounding. Similarly, replication can test for the robustness of findings from one study under alternative study conditions or alternative analyses (e.g., controlling for potential confounds not identified in the initial study).

Confounding effects may be less likely to occur and act similarly at multiple times and locations.[citation needed] In selecting study sites, the environment can be characterized in detail at the study sites to ensure sites are ecologically similar and therefore less likely to have confounding variables. Lastly, the relationship between the environmental variables that possibly confound the analysis and the measured parameters can be studied. The information pertaining to environmental variables can then be used in site-specific models to identify residual variance that may be due to real effects.[6]

Depending on the type of study design in place, there are various ways to modify that design to actively exclude or control confounding variables:[7]

• Case-control studies assign confounders to both groups, cases and controls, equally. For example if somebody wanted to study the cause of myocardial infarct and thinks that the age is a probable confounding variable, each 67 years old infarct patient will be matched with a healthy 67 year old "control" person. In case-control studies, matched variables most often are the age and sex. Drawback: Case-control studies are feasible only when it is easy to find controls, i.e., persons whose status vis-à-vis all known potential confounding factors is the same as that of the case's patient: Suppose a case-control study attempts to find the cause of a given disease in a person who is 1) 45 years old, 2) African-American, 3) from Alaska, 4) an avid football player, 5) vegetarian, and 6) working in education. A theoretically perfect control would be a person who, in addition to not having the disease being investigated, matches all these characteristics and has no diseases that the patient does not also have — but finding such a control would be an enormous task.
• Cohort studies: A degree of matching is also possible and it is often done by only admitting certain age groups or a certain sex into the study population, creating a cohort of people who share similar characteristics and thus all cohorts are comparable in regard to the possible confounding variable. For example, if age and sex are thought to be confounders, only 40 to 50 years old males would be involved in a cohort study that would assess the myocardial infarct risk in cohorts that either are physically active or inactive. Drawback: In cohort studies, the overexclusion of input data may lead researchers to define too narrowly the set of similarly situated persons for whom they claim the study to be useful, such that other persons to whom the causal relationship does in fact apply may lose the opportunity to benefit from the study's recommendations. Similarly, "over-stratification" of input data within a study may reduce the sample size in a given stratum to the point where generalizations drawn by observing the members of that stratum alone are not statistically significant.
• Double blinding: conceals from the trial population and the observers the experiment group membership of the participants. By preventing the participants from knowing if they are receiving treatment or not, the placebo effect should be the same for the control and treatment groups. By preventing the observers from knowing of their membership, there should be no bias from researchers treating the groups differently or from interpreting the outcomes differently.
• Randomized controlled trial: A method where the study population is divided randomly in order to mitigate the chances of self-selection by participants or bias by the study designers. Before the experiment begins, the testers will assign the members of the participant pool to their groups (control, intervention, parallel), using a randomization process such as the use of a random number generator. For example, in a study on the effects of exercise, the conclusions would be less valid if participants were given a choice if they wanted to belong to the control group which would not exercise or the intervention group which would be willing to take part in an exercise program. The study would then capture other variables besides exercise, such as pre-experiment health levels and motivation to adopt healthy activities. From the observer’s side, the experimenter may choose candidates who are more likely to show the results the study wants to see or may interpret subjective results (more energetic, positive attitude) in a way favorable to their desires.
• Stratification: As in the example above, physical activity is thought to be a behaviour that protects from myocardial infarct; and age is assumed to be a possible confounder. The data sampled is then stratified by age group – this means, the association between activity and infarct would be analyzed per each age group. If the different age groups (or age strata) yield much different risk ratios, age must be viewed as a confounding variable. There exist statistical tools, among them Mantel–Haenszel methods, that account for stratification of data sets.
• Controlling for confounding by measuring the known confounders and including them as covariates in multivariate analyses such as regression analysis; however, multivariate analyses reveal much less information about the strength of the confounding variable than do stratification methods.[dubious ]

All these methods have their drawbacks:

1. The best available defense against the possibility of spurious results due to confounding is often to dispense with efforts at stratification and instead conduct a randomized study of a sufficiently large sample taken as a whole, such that all potential confounding variables (known and unknown) will be distributed by chance across all study groups and hence will be uncorrelated with the binary variable for inclusion/exclusion in any group.
2. Ethical considerations: In double blind and randomized controlled trials, participants are not aware that they are recipients of sham treatments and may be denied effective treatments.[8] There is resistance to randomized controlled trials in surgery because patients would agree to invasive surgery which carry risks under the understanding that they were receiving treatment.

## References

1. ^ Johnston SC. Identifying Confounding by Indication through Blinded Prospective Review. Am J Epidemiol 2001; 154: 276–84.
2. ^ a b Pelham, Brett (2006). Conducting Research in Psychology. Belmont, Wadsworth Publishing. ISBN 0-534-53294-2.
3. ^ Steg, L., Buunk, A. P., & Rothengatter, T. (2008). Applied Social Psychology: Understanding and managing social problems. Cambridge, UK, Cambridge University Press. Chapter 4.
4. ^ Tjønneland, Anne; Morten Grønbæk, Connie Stripp and Kim Overvad (January 1999). American Society for Nutrition American Journal of Clinical Nutrition 69 (1): 49–54.
5. ^ Axelson, O (1989). "Confounding from smoking in occupational epidemiology". British Journal of Industrial Medicine 46: 505–07.
6. ^ Calow, Peter P. (2009) Handbook of Environmental Risk Assessment and Management, Wiley
7. ^ Mayrent, Sherry L (1987). Epidemiology in Medicine. Lippincott Williams & Wilkins. ISBN 0-316-35636-0.
8. ^ Emanuel, Ezekiel J; Miller, Franklin G (Sep 20, 2001). "he ethics of placebo-controlled trials--a middle ground". The New England Journal of Medicine 345 (12): 915–9.

This textbook has a nice overview of confounding factors and how to account for them in design of experiments:

• D. C. Montgomery, D.C. (2005) Design and Analysis of Experiments, 6th edition, Wiley. (Section 7-3)
 11731 videos foundNext >
 Public Health 250A - Lecture 27: Confounding I; A. ReingoldEpidemiologic Methods I. Confounding VariablesAn example of a confounding variable. Week 9 : CONFOUNDING: SOLUTION SET 1 3 2 Confounding Variables Controlling Confounding During the Design Phase of a StudyConfounders can be controlled during the design phase and the analysis phase of a study. This video will discuss several methods available to control confoun... Public Health 250B - Lecture 14: Bias - confoundingEpidemiologic Methods II. Confounding VariablesThis video defines what a confounding variable is and also shows and example. Fatherhood is confounding the baby with new sounds.BLOG: http://www.fatherhoodis.com FACEBOOK: http://www.facebook.com/fatherhoodis TWITTER: http://www.twitter.com/fatherhoodis TUMBLR: http://fatherhoodis.tum... XCOM - Impossible - Part 4 - Month 2 - Confounding Light - High speed playthrough and guide.Part 5: coming soon Read the description for more info. Playlist: https://www.youtube.com/playlist?list=PL5XHyWzRDjEFwqpbtpu0WVegS-edjqEd3&feature=view_all R... Residual Confounding in Observational StudiesResidual confounding is imcompletely controlled confounding. I'll discuss how it happens and how you can detect it in this video.
 11731 videos foundNext >
 3272 news items
 Stereogum Dirty Beaches' Alex Zhang Hungtai On Confounding Expectations (Mostly His ... Stereogum Wed, 29 May 2013 14:01:17 -0700 There is no denying that Alex Zhang Hungtai is an intense dude. As the heart and soul behind Dirty Beaches, he makes music that is equal parts beautiful, heartbreaking, and (occasionally) terrifying. After the success of 2011's Badlands — a ... Salem's confounding fight over health care Statesman Journal (blog) Sat, 01 Jun 2013 14:03:36 -0700 Salem's confounding fight over health care. Here is the current draft of Sunday's editorial, which has gone through a number of revisions: Legislators need to back off a bill aimed at penalizing Salem Health, now that the organization has offered to ... Absurdist Theatre production confounding but engaging Tyler Morning Telegraph Thu, 23 May 2013 22:04:51 -0700 Absurdist Theatre production confounding but engaging. BY STEWART SMITH ssmith@tylerpaper.com. As of this writing, it's been two full days since I watched APEX Theatre's production of “A Resounding Tinkle” and I still have no clue what to make of it. Herald Scotland John Tiffany on quitting Scotland and confounding the critics Herald Scotland Fri, 24 May 2013 19:07:54 -0700 After 23 years in Scotland, a huge back catalogue of plays, including 12 (soon to be 13) for National Theatre of Scotland, one of which, Black Watch, won him a Laurence Olivier Award and a Critics' Circle Award for Best Director, and maybe more than a ... Legislator's votes on privatization windfall confounding Standard Speaker Thu, 23 May 2013 01:13:48 -0700 Some legislators want to take a one-time windfall of cash from the sale of liquor and use it to fund education for four years. Others want to take that same money and spend it to build a bridge. State Rep. Tarah Toohil, R-116, apparently, wants to do both. Rand Paul = interesting Washington Post (blog) Tue, 18 Jun 2013 11:49:06 -0700 From his filibuster over drones to his positioning on the immigration reform bill to his well-received trips to early presidential-voting states, Paul has shown a knack for simultaneously confounding expectations and drawing press attention. And, with ... ESPNcricinfo.com Clarke's Ashes squad fragmented ESPNcricinfo.com Tue, 18 Jun 2013 14:03:11 -0700 Sporting history is littered with teams who played above their modest talent levels by binding together in collective effort and diligence, frustrating and confounding opponents with greater resources and reputations. Unfortunately for Australia's ... Ecosystem Marketplace Habitat Banking In Spain: Moving Towards The Future Ecosystem Marketplace Tue, 18 Jun 2013 10:15:14 -0700 Confounding this is a general confounding of habitat banking with more standard Command and Control models. In addition, the lack of an agreed-on name for such mechanisms also helps to create confusion regarding the habitat banking concept.
 Limit to books that you can completely read online Include partial books (book previews) .gsc-branding { display:block; }

Oops, we seem to be having trouble contacting Twitter