A Confounder is an extraneous variable whose presence affects the variables being studied so that the results do not reflect the actual relationship between the variables under study. The aim of major epidemiological studies is to search for the causes of diseases, based on associations with various risk factors.
What is a confounding in research methods?
Confounding is one of several threats to the internal validity of a research study. ( 1) Confounding is defined as a possible source of bias in studies in which an unmeasured third variable (the confounder) is related to the exposure of interest (although not causally) and causally related to the outcome of interest. (
What are potential confounders?
Potential confounders were defined as variables shown in the literature to be causally associated with the outcome (HIV RNA suppression) and associated with exposure in the source population (hunger) but not intermediate variables in the causal pathway between exposure and outcome [4,31,32].
How do you identify confounders?
Identifying Confounding
A simple, direct way to determine whether a given risk factor caused confounding is to compare the estimated measure of association before and after adjusting for confounding . In other words, compute the measure of association both before and after adjusting for a potential confounding factor.
What are the types of confounders?
- An observed association when no real association exists.
- No observed association when a true association does exist.
- An underestimate of the association (negative confounding).
- An overestimate of the association (positive confounding).
How do you deal with confounders?
- randomization (aim is random distribution of confounders between study groups)
- restriction (restrict entry to study of individuals with confounding factors – risks bias in itself)
- matching (of individuals or groups, aim for equal distribution of confounders)
What makes a confounder?
If there is a clinically meaningful relationship between an the variable and the risk factor and between the variable and the outcome (regardless of whether that relationship reaches statistical significance), the variable is regarded as a confounder.
What are confounding factors in a research study?
Confounding variables are the stowaways in a research study that can result in misleading findings about the relationship between the independent variable (IV), the input in the study , and the dependent variable (DV), the results of the study.
What are some examples of confounding variables?
For example, the use of placebos, or random assignment to groups. So you really can’t say for sure whether lack of exercise leads to weight gain. One confounding variable is how much people eat . It’s also possible that men eat more than women; this could also make sex a confounding variable.
Is time a confounding variable?
Here, we consider “time-modified confounding,” which occurs when there is a time-fixed or time-varying cause of disease that also affects subsequent treatment, but where the effect of this confounder on either the treatment or outcome changes over time.
What is a covariate example?
For example, you are running an experiment to see how corn plants tolerate drought . Level of drought is the actual “treatment”, but it isn’t the only factor that affects how plants perform: size is a known factor that affects tolerance levels, so you would run plant size as a covariate.
How do you rule out a confounding variable?
One of the method for controlling the confounding variables is to run a multiple logistic regression . You can apply binary logistics regression if the outcome (Dependent ) variable is binary (Yes/No). In logistics regression model, under the covariates include the independent and confounding variables.
What does adjusting for confounders mean?
The process of accounting for covariates is also called adjustment (similar to logistic regression model) and comparing the results of simple and multiple linear regressions can clarify that how much the confounders in the model distort the relationship between exposure and outcome .
What is an example of information bias?
Incomplete medical records. Recording errors in records . Misinterpretation of records. Errors in records, like incorrect disease codes, or patients completing questionnaires incorrectly (perhaps because they don’t remember or misunderstand the question).
What is bias in research?
In research, bias occurs when “systematic error [is] introduced into sampling or testing by selecting or encouraging one outcome or answer over others ” 7 . Bias can occur at any phase of research, including study design or data collection, as well as in the process of data analysis and publication (Figure 1).
What is confounding bias in research?
Confounding bias: A systematic distortion in the measure of association between exposure and the health outcome caused by mixing the effect of the exposure of primary interest with extraneous risk factors .
