What Selection bias is
Selection bias is a type of bias that occurs when the sample of individuals or data used in a study is not representative of the population of interest. Selection bias can lead to invalid conclusions and inaccurate results.
Steps for Selection bias:
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Identify the population of interest: The first step in addressing selection bias is to clearly define the population of interest. This includes defining the characteristics that the population should have.
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Identify the sampling method: The next step is to determine how the sample will be selected. This includes determining which sampling method will be used (e.g., random, convenience, or stratified) and how the sample will be drawn (e.g., census, probability, or non-probability).
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Determine the size of the sample: The size of the sample should be determined in order to reduce the possibility of selection bias.
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Collect the data: Once the sampling method and sample size have been determined, the data can be collected.
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Analyze the data: The data should then be analyzed to identify any potential sources of selection bias.
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Adjust the results as needed: If selection bias is identified, steps should be taken to adjust the results. This may include weighting the data or using a different sampling method.
Examples
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A survey of college students is conducted to assess job satisfaction. The sample selection process only includes students who attend prestigious universities, skewing the sample to those who are more likely to be satisfied with their job.
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A polling company conducts a survey of voters to assess the public opinion of a political candidate. The survey only includes people in the candidate’s home district, making the sample unrepresentative of the entire electorate.
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A clinical trial is conducted to test the efficacy of a new drug. The selection process for participants only includes those with a certain medical condition, excluding other potential patients who may have been affected by the drug.