WHAT ARE CONFOUNDING VARIABLES?

 Confounding variable

The variables that correlate in a positive or in a negative manner  with both the dependent variable and the independent variable are confounding variables or confounders. An external variable whose presence causes an effect in the variables which are being studied so that the results do not reflect the actual relationship between the variables under study is what we call a confounder. When no true association exists amidst them, confounding factors can mask the actual relationship between, or elaborates a supposed relationship falsely between the experiment and outcome. 

Effect of Confounding Variables

 

During a research, until and unless some appropriate methods are employed to adjust the confounders, the existence of confounding variables makes it hard to study a research in order to make a clear-precise connection amid experiment and outcomes. Therefore, an individual has to reassure that all the confounding variables have been identified in the research study in order to cut down confounding variables. It can give more accurate results if we understand confounding variables. Major research obstacles are resulted by confounding variables in the particular of increased variance and research bias. Outcomes can either become  overestimated or underestimated at the end with these researches. 

 

1. Increased Variance 

 

Increased variance is very common with research that has no control variables such that changes done in the target variables could be triggered by other variables,  if we refer to a raise in the possible number of causative and independent variables in the  research.

 

For example, it is revealed in a conducted research study, that lack of exercises can result in an increase in weight gain. Since, there is no control variable, therefore one cannot believe at the research outcome because there might be other factors that can affect the target variables as well.   

 

2. Confounding Bias

Chances of a statistical parameter to overestimate or underestimate a research parameter is what a confounding bias means.  For instance, a survey design has a transparent existence of confounding bias, it can result in huge survey dropout rates and survey response bias that again affect the research outcomes. In an experiment, a confounding might be negative  or positive in nature which leads to distortion of internal efficacy or internal validity of an experiment. When the observed connection is biased away from the null in a way that it overestimates the outcomes, then a positive confounding bias takes place. When the observed connection is biased towards the null in a way that it underestimates the outcomes, then a negative confounding bias takes place and it can even give a false rejection of a null hypothesis. 

 

3. Irrelevant Research Outcomes

 

In a research study, as an external variable, a confounding variable can change the outcome of an experiment. Both independent and dependent variables can be transformed by a third factor in a research and therefore affecting outcomes of correlational or experimental research.

 

During a research experiment, via generating the wrong research results, a confounding variable is a third factor that can influence an experiment. For instance, an incorrect correlational association between explanatory and target variables can be rendered by a third factor.