46 Non-Probability Sampling

Probably you’ve guessed it by now, right? If probability is random – NON colloquial random – the non-probability is non-random. Which is actually a lot closer to the concept of “random” as we understand it in ordinary, everyday, informal contexts. I know – potentially so confusing! Just commit to memory that Random Reduces Bias [in terms of sampling strategies]. NON-random/probability actually adds bias. So. Let’s say you’re doing your deconstruction and you head back to the original – OP – primary research. Mosey on over to the “procedure” and “participants” sections. And see that they used one of the methods below (which, PS, they do NOT always state the “name” of the strategy so you have to recognize it without the label)… SHOULD YOU BELIEVE IT? I’m not saying that you shouldn’t because getting random samples is pretty darned difficult, but you should definitely practice your critical thinking and add some of that healthy skepticism.

1. Convenience
   

• • In this specific technique, the researcher chooses those in their sampling frame that are easiest to access.
    • Ex: When deciding who to pull from a sample group you decide to pull members of your family because they are the easiest and most convenient group of people to study.  ( Example from student Kailey Brown)

   2. Volunteer 

• • With a volunteer sample, those who participate in the study choose on their own to do so.
    • Ex:  The mass emails students receive from the University of Iowa to participate in studies. Whoever wants to participate responds to the email. (Example from student Kailey Brown)

  3. Snowball 

• • This type of sampling is when someone starts the study and then refers more people to participate in it.
    • Ex: One friend finds a survey on how much coffee she drinks. She knows a lot of coffee drinker friends and wants them to participate. Then those friends want to bring in more people to contribute. (Kailey Brown)

  4. Quota

• • Like stratified sampling, quota sampling breaks up the sample into subcategories in ways the researcher determines. Different from stratified sampling though, this technique chooses people without a random strategy.
    • Ex: A researcher wants to mimic the population they are studying. The population is 70% people over 60. Therefore, the participants consisted of 70% people over 60.

  5. Network 

• • This type of sampling is when a researcher utilizes their social network to recruit participants.
    • Ex: Recruiting participants from social network sites. (Example from student Monica Bucholz)

 6. Purposive/ Purposeful 

• • In this specific technique, the researcher purposely and subjectively chooses participants based on how crucial the experiences they can share are to answering the researcher’s research questions.
    • Ex: In a study about the experiences of adopted children, the researcher chooses to interview children who have been adopted (Example from student Wesley Woods)

 7. Theoretical Construct 

• • This sampling technique is when the researcher selects participants that embody a theory they are interested in. This is usually inductive because it starts on the level of theory but then narrows in on the experience of an individual.
    • Ex: In a study about adopted children, the researcher seeks to show the struggles many children go through. The researcher chooses to sample children who have had negative experiences.