The following are examples of strong correlation caused by a lurking variable:
- The average number of computers per person in a country and that country’s average life expectancy.
- The number of firefighters at a fire and the damage caused by the fire.
- The height of an elementary school student and his or her reading level.
What are lurking variables?
In statistics, lurking variables are extraneous variables that are not considered in the analysis of a study. Learn more about the definition of lurking variables and explore the impact of lurking variables on the internal validity of a study through examples.
How do you eliminate the risk of lurking variables in research?
In observational studies, it can be very difficult to eliminate the risk of lurking variables. In most cases, the best you can do is simply identify, rather then prevent, potential lurking variables that may be impacting the study.
What is the difference between extraneous variables and lurking variables?
Extraneous variables threaten the internal validity of any study when adequate precautions are not taken. Lurking variables are a particular threat because they are usually unknown variables at the onset of a study and, for that reason, are not incorporated into the design of the study.
What are lurking variables that affect blood pressure?
Lurking variables that also affect blood pressure are whether a person smokes and stress levels. In statistical models, the error term explains lurking variables that affect the process. To discover lurking variables, you must take the time to understand your data and the important variables that can affect a process.
What is a lurking variable in a study?
A lurking variable is defined as an extraneous variable that is not included in statistical analysis.
For which variables do we find lurking variables?
A lurking variable is a variable that is unknown and not controlled for; It has an important, significant effect on the variables of interest. They are extraneous variables, but may make the relationship between dependent variables and independent variables seem other than it actually is.
Is gender a lurking variable?
In addition to the explanatory variable (method) and the response variable (success or failure), a third, lurking variable (gender) is tied in (or confounded) with the explanatory variable's values, and may itself cause the response to be success or failure.
Are there lurking variables in experiments?
A well-designed experiment includes design features that allow researchers to eliminate extraneous variables as an explanation for the observed relationship between the independent variable(s) and the dependent variable. These extraneous variables are called lurking variables.
What is a lurking variable quizlet?
Lurking Variable. A lurking variable is an explanatory variable that was not considered in a study, but that affects the value of the response variable in the study. in addition, lurking variables are typically related to explanatory variables considered in the study.
What's the difference between a lurking variable and a confounding variable?
A lurking variable is a variable that has an important effect on the relationship among the variables in the study, but is not one of the explanatory variables studied. Two variables are confounded when their effects on a response variable cannot be distinguished from each other.
What is an invisible variable?
an undiscovered causative variable. When a relationship is found between variables x and y, variable x may erroneously be thought to be the cause of y. However, the cause of y may be a hidden variable z that is correlated with variable x.
Is quality of life a hidden variable?
Quality of life is a hidden variable because it cannot be measured directly but must be inferred from measurable variables such as wealth, success, and environment.
How do you deal with lurking variables?
In most cases, the best you can do is simply identify, rather then prevent, potential lurking variables that may be impacting the study. In experimental studies, however, the impact of lurking variables can mostly be eliminated with good experimental design.
Can you think of any lurking variables that may affect the results of the study?
Yes. For example, possible lurking variables might be eating habits and the amount of exercise per week. The researchers made an effort to avoid confounding by accounting for potential lurking variables.
What are 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.
What is the difference between a lurking variable and a confounding variable?
A lurking variable is not accounted for but influences the variables being considered. A confounding variable is considered, but isn't given credit...
What is an example of a lurking variable?
A researcher finds that the average person who rides tricycles is shorter than the average person who bikes. The researcher concludes that riding a...
What is meant by a lurking variable?
A lurking variable is a hidden or unaccounted-for variable that changes the variables included in a study. Both the dependent and independent varia...
Lurking Variables Explained: Types & Examples
Lurking variables are notorious for confusing researchers especially when the outcome of a study is being analyzed. This confusion stems from whether the relationship between variables is based on cause-and-effect or just random association.
What is a Lurking Variable?
A lurking variable is defined as an extraneous variable that is not included in statistical analysis.
Effects of Lurking Variables
The effect of lurking variables arises from how they provide another interpretation for the relationship that exists between the independent and dependent variables while remaining hidden.
Examples of Lurking Variables
Even though correlation does not equal causation, there is a well-known existing relationship between shark attacks and the sales of ice cream: both of them increase in the same period.
What Problems Can Lurking Variables Cause?
Lurking variables can falsely show a strong relationship between two variables and it can also hide the relationship existing between two variables.
How to Identify a Lurking Variable
You must first identify lurking variables before you can eliminate or hold them constant
Difference between a Confounding and Lurking Variable?
In a lurking variable, two variables become confounded when their effects on a response or dependent variable cannot be distinguished from each other. However, the confounding variable is not only present in the study but is related to the other study variables.
What Is a Lurking Variable?
A lurking variable is a variable that is hidden or not included in an analysis, but impacts the relationship being analyzed. Some lurking variables hide real relationships, while others can make a false relationship appear to exist. Either way, lurking variables create misleading study results.
Lurking Variable vs. Confounding Variable
While a lurking variable is hidden and not considered in the research study, a confounding variable is considered and present in the study. Both can influence the relationship between the variables. For example, if a researcher is looking for a relationship between A and B, they might also check for a relationship with C.
What is lurking variable?
Lurking variables are one kind of extraneous variable. They are neither of the variables under investigation (explanatory and response variables), but some other random variables that influences one or both. These random third variables are called lurking variables because they go unnoticed by lurking beneath the surface of the variables ...
Why are lurking variables often discovered after the fact?
Because lurking variables are often discovered after-the-fact, they likely were not measured nor observed. Without knowing precisely how much the additional variable accounts for variation in the response variable, it is impossible to say how much is attributed to the explanatory variable alone. Lesson Summary.
Why are extraneous variables considered a threat?
Extraneous variables threaten the internal validity of any study when adequate precautions are not taken. Lurking variables are a particular threat because they are usually unknown variables at the onset of a study and, for that reason, are not incorporated into the design of the study.
What is the third variable that causes the similar response?
The third variable that causes the similar response may or may not be a lurking variable. Internal validity is the extent to which we can conclude the results of a study are reliable and valid. When a study has a strong internal validity, we can say that the research answered the research question asked.
What is a common response variable?
Common response variables are variables that respond similarly to a third variable. That third variable could be the explanatory variable under investigation or an unknown lurking variable. Extraneous variables are a threat to a study's internal validity. This is the extent to which we can conclude the results of a study are reliable and valid.
What is the purpose of extraneous variables?
The goal of any research study is to demonstrate cause and effect relationships between one or more independent (explanatory) and dependent (response) variables. Extraneous variables are variables that co-vary with the explanatory variable and/or the response variable, making it difficult to conclude that it was the explanatory variable alone ...
What are lurking variables? What are some examples?
What Are Some Examples of a Lurking Variable? Two examples of lurking variables are the color of a paper airplane and its ability to fly and the size of the thymus in children who developed SIDS in the early 1900s. Neither of the two factors are responsible for either effect.
What is lurking variable?
A lurking variable is an extraneous variable that does not play a role in determining the relationship between the independent and the dependent variable. A variable is any factor that can be controlled, changed or measured in an experiment. There are several types of variables used ...
What is a variable in an experiment?
A variable is any factor that can be controlled, changed or measured in an experiment. There are several types of variables used to report the data collected from an experiment. The most-common types of variables are the independent, dependent, controlled and extraneous variables.
What is controlled variable?
A controlled variable is a constant variable that does not change during an experiment. Extraneous variables are variables that are considered extra in an experiment. They may influence the outcome of the experiment, but they aren't always taken into serious account.
What is the difference between independent and dependent variables?
The independent variable is the variable or condition that the experimenter changes and controls during the experiment. The dependent variable is what is measured or obtained during the experiment. It is dependent upon the independent variable and its varying states.
