CONTROL TECHNIQUES
Controlling variance of confounding variables:
In Experimental Settings :
1. Conducting the experiment in a controlled environment ( e.g.,laboratory),
2. Subject selection (e.g., matching subjects in experiments)
3. Random assignments of subjects ( variation of confounding variables are evenly distributed between the experimental and control group )
? In Survey Research:
1. Sample selection (e.g., including only subjects with appropriate characteristics – using male college graduates as subjects will control for potential confounding effects of gender and education)
2. Statistical Control
Moderating
In each relationship there is one Independent Variable (IV) & one Dependent Variable (DV)
Four day work week (IV) will lead to higher productivity (DV).
Moderating variable is a second independent variable that has significant effect on the originally stated IV–DV relationship.
Four day work week (IV) will lead to higher productivity (DV), especially among young workers (MV)
Some of the points you can also refer from this links:
Randomization
It is a statistical control technique designed to ensure that extraneous variable will not systematically bias the study results;
It is done by equating groups of participants-ensuring that every member has an equal chance of being assigned to any group.
Eg. Randomized group design and randomized block design
Randomization: an important method of controlling extraneous variables is randomization. It is considered to be the most effective way to control the variability due to all possible extraneous sources. If through randomization has been achieved then the treatment groups in the experiment could be considered statistically equal in all possible ways. Randomization is a powerful method of controlling variable. In other words it is a procedure for equating groups with respect to secondary variable. Randomization means random selection of the experimental units from the larger population. Random assignment means that every experimental unit has an equal chance of being placed in any of the treatment conditions or groups. In using randomization method some problems may be encountered. It is possible to select a random sample from a population, but then assignment of experimental units to groups may get biased. Random assignment of subjects is critical to internal validity. If subjects are not assigned randomly, confounding may occur.
Randomized group design and randomized block design are the examples of research design in which randomization is used to control the extraneous variable.
Statistical control:
Statistically controlling for extraneous variables is an option for removing the influence of the variable on the study design.
Evaluators need to collect data on the extraneous variables, as well as the independent and dependent variables for analysis.
Evaluators can use a range of statistical techniques for control including:
General Linear Model
Analysis of covariance
Blocking
blocking is the arranging of experimental units in groups (blocks) that are similar to one another.
Blocking reduces unexplained variability.
Blocking used for nuisance factors that can be controlled. (reduce exptl error)
Examples
Male and Female:
Elevation --high or low
Intervention
Randomized block design
The general rule is:
“Block what you can; randomize what you cannot.”
Matching
It is used to control the extraneous source of variance.
Matching is a statistical technique which is used to evaluate the effect of a treatment by comparing the treated and the non-treated units in an experiment.
Matching enables a comparison of outcomes among treated and non-treated units to estimate the effect of the treatment reducing bias due to confounding.
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