extraneous, third variable called a confounder. Since the exposure of interest is rarely the only factor that differs between exposed and unexposed groups, and that also affects the health outcome or disease frequency, confounding is a common occurrence in etiologic studies. Confounding is also a form a bias. Confounding is a bias because it
The term "confounding" refers to the presence of A) a variable which is controlled and does not affect the outcome of a study. B) two independent variables in a study. C) a variable that is not controlled which affects the outcome of a study. D) two dependent variables in a study.

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(C) State and operationally define an independent variable and a dependent variable that corresponds to your hypothesis. Finally, identify at … Continue reading “In your own words, please define the following terms: independent variable, dependent variable, extraneous variable, and confounding variable” A confounding variable is an example of systematic error, whereas an extraneous variable is an example of random error. A confounding variable is a variable other than the independent variable that is found to vary systematically among the conditions. The systematic error varies among the conditions, so it is a confounding variable.

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or measurement of those extraneous variables and adjustment in the analysis (e.g., calculating the effect of air pollution with adjustment for cigarette smok-ing). Although such control without randomization is challenging, an awareness of the possible confounding factors enables the investigator to design and conduct the study to minimize such ...

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Confounding is when a researcher does not control some extraneous variables that may influence the resultsthe only variable that should influence the results is the variable being studied. This is a very serious problem since the researcher can't really claim that he/she established cause and effect.

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An observed variable is one that is actually measured. For example, a student’s score on a test or a subscale is an observed variable. In contrast, latent variables are the hypothetically existing con-structs of interest in a study. Examples of latent variables include peace, intelligence, and apathy. Latent variables cannot be directly measured.

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In the ideal experiment there would be no variables of types 3 and 4, and presumably, any changes in Y could be ascribed to changes in X. Kish’s type 3 and type 4 variables are more commonly called confounding variables (also known as extraneous or lurking, and sometimes simply called a confound). The article explains that the terms extraneous, nuisance, and confounding variables refer to any variable that can interfere with the ability to establish relationships between independent ...

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A confounding variable is a variable that correlates with both your regressor and the dependent variable. In some way, this second predictor variable explains all or part of the dependent variable and also is reflected in the independent variable.

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Compare and contrast extraneous variables with confounding variables. Both types of variables have the potential to interfere with the relationship between the independent and dependent variable. Extraneous variables aren't included in the study but can still influence the results of the study if unaccounted for or if not controlled.

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