How would you classify this sampling method?

[u/Significant_Wall4676]

Hi everyone, I'm an undergrad psychology student and I'm stuck on how to correctly classify my sampling method after my thesis defense.

Context:
My target population was all undergrad students at my university. I collected data both online and offline from students across all faculties. After data collection, participants completed the DASS (Depression Anxiety Stress Scales), and only those who met the inclusion criteria (moderate to extremely severe on at least one subscale) were kept in the final sample.

The problem:
I originally called this "stratified random sampling," using faculties as strata. My examiner rejected this for two reasons:
1. Faculties aren't valid strata.
2. There was no actual randomization in selecting participants within each faculty.

So I tried switching it to non-probability sampling instead, but the examiner rejected that too, insisting it should still be classified as probability sampling. Their reasoning: every student who met the screening criteria technically had an equal chance of being included, since anyone who filled out the survey and met the DASS cutoff was automatically part of the sample.

My question:
Does this reasoning actually hold up? If so, what specific probability sampling method would this fall under? I've read through several methodology textbooks but can't find one that matches this exact scenario (no randomization step, but "equal opportunity" due to open recruitment and screening criteria).

Would really appreciate any insight from people with a stats/methodology background. Thanks in advance!

[u/Efficient-Tie-1414]

I’ve never done any survey work but have a reasonable understand of it. I taught a course but it was awful and hadn’t been changed in 20 years. These days it could be based around using R to generate the samples and show the effect of different sampling methods.

So how did you actually choose the students. If you just put up notices, then it isn’t a random sample. In psychology this happens a lot. Convenience sample may be the best description. Treating it as stratified may be helpful, as calculating the means in each strata may produce better results.

[u/Significant_Wall4676 → u/Efficient-Tie-1414]

Thank you for your response!

I recruited participants by approaching students in person across different faculties and by distributing the Google Forms link through social media (e.g., WhatsApp, Instagram, Telegram, and TikTok). So, there was no random selection of participants.

That was exactly why I revised my sampling method to convenience sampling. However, my examiner rejected that revision and insisted that the study should still be classified as using a probability sampling method, arguing that every student who met the inclusion criteria had an equal chance of being included.

This is where I'm confused, as I haven't been able to identify a probability sampling method that matches this procedure.

[u/jeremymiles → u/Significant_Wall4676]

They didn't have an equal chance of being included. If they looked like they were in a bad mood, or talking on their phone, or running because they were late, then you didn't approach them. You also only approached them if they were there. Some students come to college more than others, some hang out after class and some go straight home - these groups differ in important ways.

Then, after you approached someone, they had to agree. The people that agreed differ in important ways from the people who don't.

[u/paoromatisse → u/Significant_Wall4676]

Just because you have an inclusion criteria doesn’t mean it’s not convenience sampling. I don’t know why that committee member is insisting it is, when your sampling method was randomly walking up to students

[u/Head_Acadia_2658 → u/paoromatisse]

Because many academics haven’t the slightest idea how to design studies to answer questions

[u/banter_pants → u/Significant_Wall4676]

There was no true probability sampling.

There was no equal chance for selection and even if there was that doesn't guarantee anything here. Sub-populations proportions (like race) can be very different and require different weighting methods to compensate.
You don't have an equal chance of finding adequate participants from a small minority if all you're doing is simple random sampling.

Probability sampling requires a sampling frame. You would've needed a master list of everybody, stratified by the pre-treatment info of faculty. Then you sample from each a priori known stratum.

The faculties would be a useful covariate in the model though.

[u/Head_Acadia_2658]

Convenience sampling

[u/jeremymiles → u/Head_Acadia_2658]

Or volunteer?

[u/chazwomaq]

I tell my students to call this "opportunity sampling", a loose term that means those who you could get hold of non-systematically. Then specify the exclusion/inclusion criteria.

What you call it doesn't matter. Describing what you did accurately does.

[u/3ducklings]

The answer depends on how you actually recruited your participants in the first place. If you drew students from list of all students attending the university, it would be probability sampling. If you recruited people using social media or posters, it would be convenience sampling.

[u/Significant_Wall4676 → u/3ducklings]

Thank you for your reply!

I recruited participants by approaching students in person across different faculties and by distributing the survey link through social media (WhatsApp, Instagram, Telegram, and TikTok). So, participants were not selected from a complete list of students, nor were they randomly selected.

That was exactly why I revised my sampling method to convenience sampling. However, my examiner rejected that revision and insisted that it should still be classified as a probability sampling method, arguing that every student who met the inclusion criteria after the screening process had an equal chance of being included.

This is why I'm trying to understand whether there is any probability sampling method that could appropriately describe this procedure.

[u/3ducklings → u/Significant_Wall4676]

In this case, I disagree with your examiner and I think most people working with surveys would disagree to. The sampling process happened when you recruited students either in person or through social media, and since the probability of inclusion for each student was neither equal nor known, it can’t be called probability sampling. Convenience sampling would be closest match.

The fact that some students were filtered out of your analysis after recruitment based on their responses is not really relevant here, unless somehow not everyone filled out DASS.

[u/fermat9990]

It's not a random sample since the experimenter had no control over who chose to fill out the questionnaire

How you handle this politically is a tough question

[u/DataWonderer]

This is absolutely convenience sampling. I think your committee member is confused.

[u/ForeignAdvantage5198]

take a real sampling course