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A variable in an experiment which is held constant in order to assess the relationship between multiple variables [a], is a control variable. [2] [3] A control variable is an element that is not changed throughout an experiment because its unchanging state allows better understanding of the relationship between the other variables being tested.
A scientific control is an experiment or observation designed to minimize the effects of variables other than the independent variable (i.e. confounding variables). [1] This increases the reliability of the results, often through a comparison between control measurements and the other measurements. Scientific controls are a part of the ...
The change in one or more independent variables is generally hypothesized to result in a change in one or more dependent variables, also referred to as "output variables" or "response variables." The experimental design may also identify control variables that must be held constant to prevent external factors from affecting the results ...
To address nuisance variables, researchers can employ different methods such as blocking or randomization. Blocking involves grouping experimental units based on levels of the nuisance variable to control for its influence. Randomization helps distribute the effects of nuisance variables evenly across treatment groups.
A clinical control group can be a placebo arm or it can involve an old method used to address a clinical outcome when testing a new idea. For example in a study released by the British Medical Journal, in 1995 studying the effects of strict blood pressure control versus more relaxed blood pressure control in diabetic patients, the clinical control group was the diabetic patients that did not ...
In this case, the control variables may be wind speed, direction and precipitation. If the experiment were conducted when it was sunny with no wind, but the weather changed, one would want to postpone the completion of the experiment until the control variables (the wind and precipitation level) were the same as when the experiment began.
A controlled experiment often compares the results obtained from experimental samples against control samples, which are practically identical to the experimental sample except for the one aspect whose effect is being tested (the independent variable). A good example would be a drug trial.
Difference in differences (DID [1] or DD [2]) is a statistical technique used in econometrics and quantitative research in the social sciences that attempts to mimic an experimental research design using observational study data, by studying the differential effect of a treatment on a 'treatment group' versus a 'control group' in a natural experiment. [3]