Undercoverage vs Nonresponse Bias
Both terms below come up in the same part of the course, and students mix them up. Here is each one defined on its own, side by side, so you can see where they part company.
Undercoverage
Collecting data and study design
Undercoverage is a form of sampling bias that occurs when some groups in the population are left out or underrepresented by the sampling method.
Undercoverage happens when the method used to reach people systematically misses part of the population. For example, a telephone survey conducted only on landlines undercovers younger adults, who mostly use cell phones. Because the missing groups may differ from those included, the sample statistic can be pushed away from the true parameter. Using a sampling frame that covers the whole population helps reduce it.
Nonresponse bias
Collecting data and study design
Nonresponse bias occurs when people chosen for the sample do not respond, and those who do respond differ systematically from those who do not.
Nonresponse bias arises after the sample is chosen, when some selected people do not answer. For example, if a survey reaches a random sample but only the most satisfied customers reply, the results skew positive. The problem is not the missing answers themselves but that non-responders tend to differ from responders. Unlike undercoverage, which happens before contact, nonresponse occurs after people have been selected.