How can you recruit representative samples for public opinion research?

1 Define your sampling frame

The sampling frame is the list of units or individuals from which you will draw your sample. It should be as close as possible to the population of interest, and exclude any irrelevant or ineligible cases. For example, if you want to measure the opinion of voters in a city, your sampling frame should include only registered voters who live in that city. You can use various sources to create your sampling frame, such as electoral rolls, census data, administrative records, or online directories.

2 Choose your sampling method

The sampling method is the technique or procedure that you will use to select your sample from the sampling frame. There are two main types of sampling methods: probability and non-probability. Probability sampling means that every unit or individual in the sampling frame has a known and equal chance of being selected, which ensures statistical representativeness and generalizability. Non-probability sampling means that the selection is based on some criteria other than chance, such as convenience, availability, or self-selection, which may introduce bias and limit inference. The most common probability sampling methods are simple random sampling, stratified sampling, cluster sampling, and systematic sampling. The most common non-probability sampling methods are quota sampling, purposive sampling, snowball sampling, and convenience sampling.

4 Recruit your sample

The recruitment process is the way that you will invite or contact the units or individuals in your sample to participate in your research. It should be clear, ethical, and respectful, and follow the principles of informed consent. You can use different modes of recruitment, such as phone calls, emails, letters, online platforms, social media, or face-to-face interactions. You should also consider the response rate, which is the percentage of units or individuals who agree to participate in your research out of those who are contacted. To increase the response rate, you can use various strategies, such as offering incentives, sending reminders, providing clear instructions, and building rapport.

5 Monitor and adjust your sample

The final step is to monitor and adjust your sample as you collect your data. You should check the quality and consistency of your data, and identify any errors, missing values, outliers, or duplicates. You should also compare your sample characteristics with the population characteristics, and assess the level of representativeness and balance. If you find any discrepancies or gaps, you may need to adjust your sample by adding, removing, or weighting some cases, or by applying some statistical techniques, such as post-stratification or calibration. However, you should be careful not to over-adjust your sample, as it may affect the validity and reliability of your results.