Confounding variables
Adjust the outcome variable for differences in secondary, tertiary, or ancillary variables
A confounding variable is the variable that mediates, changes or adjusts the relationship between independent and dependent variables. Within applied statistics and research, this variable can be categorical (dummy coding), ordinal (dummy coding), or continuous (covariate).
Confounding variables, both measured and unmeasured, must be taken into account in order to yield valid and causal effects. Random selection and random assignment are used in experimental designs to account for confounding variables and allow for the assumption of equipoise (treatment groups are similar at baseline).
Confounding variables, both measured and unmeasured, must be taken into account in order to yield valid and causal effects. Random selection and random assignment are used in experimental designs to account for confounding variables and allow for the assumption of equipoise (treatment groups are similar at baseline).
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