peittävyysvirheitä

Peittävyysvirheitä, known in English as coverage errors, refers to inaccuracies in statistical surveys that arise when the sampling frame does not accurately represent the target population. This can occur in several ways. One primary cause is undercoverage, where certain segments of the population are inadequately represented or entirely excluded from the sampling frame. For example, if a survey uses a phone directory as its sampling frame, individuals without landlines might be systematically excluded, leading to undercoverage. Conversely, overcoverage happens when elements outside the target population are included in the sampling frame. This could involve listing individuals who have moved away or deceased individuals in a population registry.

The consequences of peittävyysvirheitä can significantly impact the validity and reliability of survey results. If the under- or overcovered groups have characteristics that differ from the rest of the population, the survey estimates will be biased. This means the results will systematically deviate from the true population values. For instance, if a survey on consumer habits excludes younger demographics due to undercoverage in its sampling frame, the findings about purchasing trends might not accurately reflect the behavior of the entire consumer market. Researchers strive to minimize coverage errors through careful design of sampling frames, using multiple sources where appropriate, and employing post-survey adjustments to account for known discrepancies.