Examples of lurking variables
What is lurking variable in research?
What is a Lurking Variable? 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.
Is age a lurking variable?
The lurking variable here, though, is actually age. The more times someone’s been married, the older they’re likely to be, and age is a way to predict how close someone is to death.
What are examples of hidden variables?
Hidden Variables. A public health student gathers data on bottled water use in her state. Her data indicate that households that use bottled water have healthier children than households that don’t. She concludes that drinking bottled water instead of tap water helps to prevent childhood diseases.
Is weather a confounding variable?
A confounding variable would be any other influence that has an effect on weight gain. Amount of food consumption is a confounding variable, a placebo is a confounding variable, or weather could be a confounding variable. Each may change the effect of the experiment design.
What is a hidden variable in statistics?
Hidden variables may refer to: Confounding, in statistics, an extraneous variable in a statistical model that correlates (directly or inversely) with both the dependent variable and the independent variable.
What type of variable is gender?
categorical variable
For example, gender is a categorical variable having two categories (male and female) with no intrinsic ordering to the categories. An ordinal variable has a clear ordering.
What is a lurking and 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. Confounding. Two variables are confounded when their effects on a response variable cannot be distinguished from each other.
Is gender discrete or continuous?
Discrete Categorical
Variable Reference Table : Few Examples
| Variable | Variable Type | Variable Scale |
|---|---|---|
| Gender | Discrete | Categorical |
| Gender as Binary 1/0 Coding | Discrete | Categorical |
| True/False | Discrete | Categorical |
| Phone Number | Discrete | Nominal |
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7 oct 2016
Is gender a social construct?
Gender refers to the characteristics of women, men, girls and boys that are socially constructed. This includes norms, behaviours and roles associated with being a woman, man, girl or boy, as well as relationships with each other. As a social construct, gender varies from society to society and can change over time.
What is a lurking variable quizlet?
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 problems can lurking variables cause?
A lurking variable can hide the true relationship between variables or it can falsely cause a relationship to appear to be present between variables. Essentially, lurking variables can cause the results of a study to be misleading.
How do you control lurking variables?
Lurking variables cannot be controlled for, as they are unexpected, so it is a matter of bad luck, if they occur.
Which situations are examples of confounding variables in a study quizlet?
Example: Participant may think that the researcher is too young to be credible. Psychological characteristics if the researcher can affect the behavior of the participants. Example: Personality may be off putting or researcher may be in a bad mood.
Does a television in the bedroom cause a higher body mass index?
After adjusting for television and movie viewing times, video-game playing, parental demandingness and responsiveness, and sociodemographic factors, the presence of a bedroom television was still associated with a 0.57 (95% CI, 0.31-0.82) larger BMI at year 2 and 0.75 (0.38-1.12) larger BMI at year 4.
Which of the following is an example of an observational study quizlet?
Which of the following is an example of an observational study? Researchers ask people how long they normally sleep every night. Researchers then determine if fewer hours of sleep at night is associated with an increased likelihood of being overweight.
Which type of study has the most trouble with confounding variables?
However, of all study designs, ecological studies are the most susceptible to confounding, because it is more difficult to control for confounders at the aggregate level of data. In all other cases, as long as there are available data on potential confounders, they can be adjusted for during analysis.
What is a confounding variable in psychology?
Confounding variables in psychology are defined as influences that interfere with an accurate measurement between the independent and dependent variable.
Which of the following is true of confounding variables?
Yeah, for the answer, the answer is a confounding variable creates an association that is misleading. This is the correct choice for the answer. That is a confounding variable creates an association that is misleading as confounded as can bias your study results and lead to erroneous conclusions here.
Is age a confounding or extraneous variable?
To return to the example, age might be an extraneous variable. The researchers could control for age by making sure that everyone in the experiment is the same age. If they didn’t, age would become a confounding variable.
What is an example of confounding?
For example, a study looking at the association between obesity and heart disease might be confounded by age, diet, smoking status, and a variety of other risk factors that might be unevenly distributed between the groups being compared.