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Type II statistical error in a study comparing 2 drug treatment regimens occurs when:

  1. The control drug is not a 'gold standard' treatment.

  2. A statistically significant difference exists but the difference is not clinically important.

  3. The population under investigation does not represent the population with the disease.

  4. The data shows no difference between 2 treatment regimens and a difference actually does exist.

The correct answer is: The data shows no difference between 2 treatment regimens and a difference actually does exist.

Type II statistical error, also known as a false negative, occurs when a difference truly exists between two treatments, but the data incorrectly concludes that there is no difference. This can happen for a variety of reasons, such as a small sample size or measurement errors. The other options do not directly describe Type II statistical error. Option A refers to the control drug not being a reliable comparison, option B describes a statistically significant but not clinically important difference, and option C mentions a potential sampling bias. These factors could all impact the validity of a study, but they do not specifically describe Type II statistical error.