Question

Describe the following:

1. What is a confounding variable?

2. Define a placebo effect in a statistical study.

3. Why do researchers use randomization in statistical studies

Answer 1

1)

Confounding variables (aka third variables) are variables that the researcher failed to control, or eliminate, damaging the internal validity of an experiment.

Confounding Variable A confounding variable is an outside influence that changes the effect of a dependent and independent variable. This extraneous influence is used to influence the outcome of an experimental design. Simply, a confounding variable is an extra variable entered into the equation that was not accounted for. Confounding variables can ruin an experiment and produce useless results. They suggest that there are correlations when there really are not. In an experiment, the independent variable generally has an effect on the dependent variable. For example, if you are researching whether a lack of exercise has an effect on weight gain, the lack of exercise is the independent variable and weight gain is the dependent variable. A confounding variable would be any other influence that has an effect on weight gain. Amount of food consumption is a confounding variable, a placebo is a confounding variable, or weather could be a confounding variable. Each may change the effect of the experiment design

Example of Confounding Variable:

Weather

Another example is the correlation between murder rate and the sale of ice-cream. As the murder rate raises so does the sale of ice-cream. One suggestion for this could be that murderers cause people to buy ice-cream. This is highly unlikely. A second suggestion is that purchasing ice-cream causes people to commit murder, also highly unlikely. Then there is a third variable which includes a confounding variable. It is distinctly possible that the weather causes the correlation. While the weather is icy cold, fewer people are out interacting with others and less likely to purchase ice-cream. Conversely, when it is hot outside, there is more social interaction and more ice-cream being purchased. In this example, the weather is the variable that confounds the relationship between ice-cream sales and murder.

2)

The placebo effect is when a medical intervention results in a positive outcome. It results from the person’s anticipation that the pill or potion will be beneficial, rather than any property of the drug itself. In other words, patients who are more optimistic about an outcome are more likely to have positive outcomes.

In the past, the “placebo effect” was used with derision; people who reported benefits from a suspect, unproven or non-existent treatment (i.e. a sugar pill) were thought to be lying, inauthentic or even delusional. However, modern research is showing that objective changes in brain chemistry (for example, a release of endorphin) are linked to placebos. Interestingly, the placebo effect is even seen in patients who are informed that they are taking placebos.

How much a placebo affects someone depends upon many factors, including:

• The condition being treated.
• How strongly the person believes the placebo will help.
• How subjective the response is. The more subjective the patient’s experience is (for example, a pain scale of 1 to 10), the more likely the placebo effect is to work.
• Several other factors.

3)

.Why do researchers use randomization in statistical studies?

This ensures that each participant or subject has an equal chance of being placed in any group. Random assignment of participants helps to ensure that any differences between and within the groups are not systematic at the outset of the experiment.