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Typically, demand characteristics are considered an extraneous variable, exerting an effect on behavior other than that intended by the experimenter. Pioneering research was conducted on demand characteristics by Martin Orne. [2]
Such variables may be designated as either a "controlled variable", "control variable", or "fixed variable". Extraneous variables, if included in a regression analysis as independent variables, may aid a researcher with accurate response parameter estimation, prediction, and goodness of fit, but are not of substantive interest to the hypothesis ...
By using one of these methods to account for nuisance variables, researchers can enhance the internal validity of their experiments, ensuring that the effects observed are more likely attributable to the manipulated variables rather than extraneous influences. In the first example provided above, the sex of the patient would be a nuisance variable.
This means that extraneous variables are important to consider when designing experiments, and many methods have emerged to scientifically control them. For this reason, many experiments in psychology are conducted in laboratory conditions where they can be more strictly regulated. Alternatively, some experiments are less controlled.
When conducting experiments in psychology, some believe that there is always a trade-off between internal and external validity— having enough control over the situation to ensure that no extraneous variables are influencing the results and to randomly assign people to conditions, and; ensuring that the results can be generalized to everyday ...
Confounding is defined in terms of the data generating model. Let X be some independent variable, and Y some dependent variable.To estimate the effect of X on Y, the statistician must suppress the effects of extraneous variables that influence both X and Y.
By controlling for the extraneous variables, the researcher can come closer to understanding the true effect of the independent variable on the dependent variable. In this context the extraneous variables can be controlled for by using multiple regression. The regression uses as independent variables not only the one or ones whose effects on ...
Simple mediation model. The independent variable causes the mediator variable; the mediator variable causes the dependent variable. In statistics, a mediation model seeks to identify and explain the mechanism or process that underlies an observed relationship between an independent variable and a dependent variable via the inclusion of a third hypothetical variable, known as a mediator ...