Confounding variables are factors other than the independent variable that may cause a result. In your caffeine study, for example, it is possible that the students who received caffeine also had more sleep than the control group. Or, the experimental group may have spent more time overall preparing for the exam.
What is a confounding in psychology?
confound. n. in an experiment, an independent variable that is conceptually distinct but empirically inseparable from one or more other independent variables. Confounding makes it impossible to differentiate that variable’s effects in isolation from its effects in conjunction with other variables.
What are the types of confounding variables?
Here are some confounding variables that you need to be looking out for in experiments:
- Order Effects.
- Participant variability.
- Social desirability effect.
- Hawthorne effect.
- Demand characteristics.
- Evaluation apprehension.
How do you identify a confounding variable?
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 confounding variables in psychology examples? – Related Questions
What is a confounding variable simple definition?
Confounding variables are those that affect other variables in a way that produces spurious or distorted associations between two variables. They confound the “true” relationship between two variables.
What makes a variable confounding?
A confounding variable (confounder) is a factor other than the one being studied that is associated both with the disease (dependent variable) and with the factor being studied (independent variable). A confounding variable may distort or mask the effects of another variable on the disease in question.
What are the 3 main characteristics of a confounder?
Criteria for Confounders
- The variable must be statistically associated with the exposure.
- The variable must cause the outcome.
- The variable must not be on a causal pathway.
Is gender a confounding variable?
Numerical example
Two variables (e.g., age and gender) were considered potential confounding variables, because both were known risk factors for the outcome of interest.
Is age a confounding variable?
Age is a confounding factor because it is associated with the exposure (meaning that older people are more likely to be inactive), and it is also associated with the outcome (because older people are at greater risk of developing heart disease).
What are the 3 criteria for categorizing a confounding?
This paper explains that to be a potential confounder, a variable needs to satisfy all three of the following criteria: (1) it must have an association with the disease, that is, it should be a risk factor for the disease; (2) it must be associated with the exposure, that is, it must be unequally distributed between
How do you identify extraneous and confounding variables?
An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study. A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.
How do you control a confounding variable in an experiment?
There are several methods you can use to decrease the impact of confounding variables on your research: restriction, matching, statistical control and randomization. In restriction, you restrict your sample by only including certain subjects that have the same values of potential confounding variables.
Is age a confounding variable?
Age is a confounding factor because it is associated with the exposure (meaning that older people are more likely to be inactive), and it is also associated with the outcome (because older people are at greater risk of developing heart disease).
How can you tell if a research study has a confounding vs extraneous variable?
An extraneous variable is any variable that you’re not investigating that can potentially affect the dependent variable of your research study. A confounding variable is a type of extraneous variable that not only affects the dependent variable, but is also related to the independent variable.
Is IQ a confounding variable?
Because IQ also differs across conditions, it is a confounding variable.
How do confounding variables affect validity?
Confounding Variables
This means that as the independent variable changes, the confounding variable changes along with it. Failing to take a confounding variable into account can lead to a false conclusion that the dependent variables are in a causal relationship with the independent variable.
How does a confounding variable affect the findings of a research study?
A confounding variable, in simple terms, refers to a variable that is not accounted for in an experiment. It acts as an external influence that can swiftly change the effect of both dependent and independent research variables; often producing results that differ extremely from what is the case.
What problems can confounding variables cause?
A confounding variable is an “extra” variable that you didn’t account for. They can ruin an experiment and give you useless results. They can suggest there is correlation when in fact there isn’t. They can even introduce bias.
How do confounding factors impact outcomes?
Confounding factors may mask an actual association or, more commonly, falsely demonstrate an apparent association between the treatment and outcome when no real association between them exists.
What are confounding variables a threat to?
A variable is considered to be confounding because it provides an alternative explanation for your results; that is, an alternative explanation for the relationship or differences between the variables and/or groups that you are measuring. This threatens the internal validity of your results.
