Sample size in qualitative research? (2023)

What should be the sample size for qualitative research?

Sample Size for Qualitative Studies

Need to ensure there is enough, but not too much, data (>30 too large; Boddy, 2016). One review identified that samples of 20 and 30 (and multiples of 10) were most common (Mason, 2010), with 25-30 being a typical recommendation (Dworkin, 2012).

Ensuring you've hit the right number of participants

In The logic of small samples in interview-based, authors Mira Crouch and Heather McKenzie note that using fewer than 20 participants during a qualitative research study will result in better data.

While some experts in qualitative research avoid the topic of “how many” interviews “are enough,” there is indeed variability in what is suggested as a minimum. An extremely large number of articles, book chapters, and books recommend guidance and suggest anywhere from 5 to 50 participants as adequate.

What is sample size and why is it important? Sample size refers to the number of participants or observations included in a study. This number is usually represented by n. The size of a sample influences two statistical properties: 1) the precision of our estimates and 2) the power of the study to draw conclusions.

It has previously been recommended that qualitative studies require a minimum sample size of at least 12 to reach data saturation (Clarke & Braun, 2013; Fugard & Potts, 2014; Guest, Bunce, & Johnson, 2006) Therefore, a sample of 13 was deemed sufficient for the qualitative analysis and scale of this study.

Guest et al. (2006) found that in homogeneous studies using purposeful sampling, like many qualitative studies, 12 interviews should be sufficient to achieve data saturation.

Too small a sample may prevent the findings from being extrapolated, whereas too large a sample may amplify the detection of differences, emphasizing statistical differences that are not clinically relevant.

A sample size of 30 often increases the confidence interval of your population data set enough to warrant assertions against your findings.4 The higher your sample size, the more likely the sample will be representative of your population set.

Sandelowski [4] recommends that qualitative sample sizes are large enough to allow the unfolding of a 'new and richly textured understanding' of the phenomenon under study, but small enough so that the 'deep, case-oriented analysis' (p.

He also reminds us that in qualitative research of the “grounded theory” type, having 25 to 30 participants is a minimum to reach saturation.

What is a sampling frame for qualitative research?

A sampling frame is a researcher's list or device to specify the population of interest. It's a group of components that a researcher can use to select a sample from the population. Limited resources and accessibility might prohibit researchers from collecting data from all target population segments.

Purposeful sampling is widely used in qualitative research for the identification and selection of information-rich cases related to the phenomenon of interest. Although there are several different purposeful sampling strategies, criterion sampling appears to be used most commonly in implementation research.

Data from Likert scales and continuous (e.g. 1-10) rating scales are quantitative. These scales assume equal intervals between points.

The larger the sample size, the more accurate the average values will be. Larger sample sizes also help researchers identify outliers in data and provide smaller margins of error.

In advising graduate students we often suggest aiming for a sample of loosely around 30. This medium size subject pool offers the advantage of penetrating beyond a very small number of people without imposing the hardship of endless data gathering, especially when researchers are faced with time constraints.

Qualitative studies aim for insights: to identify usability issues in an interface. Researchers must use judgment rather than numbers to prioritize these issues. (And, to hammer home the point: the 5-user guideline only applies to qualitative, not to quantitative studies.]

The main drawback of qualitative research is that the process is time-consuming. Another problem is that the interpretations are limited. Personal experience and knowledge influence observations and conclusions. Thus, a qualitative research might take several weeks or months.

Onwuegbuzie (2003) discussed two main types of effect size for qualitative research. One is what he called manifest effect sizes, which can be used for observable data.

“A minimum of 30 observations is sufficient to conduct significant statistics.” This is open to many interpretations of which the most fallible one is that the sample size of 30 is enough to trust your confidence interval.

Which test to use if sample size is less than 30?

The parametric test called t-test is useful for testing those samples whose size is less than 30.

For example, when we are comparing the means of two populations, if the sample size is less than 30, then we use the t-test. If the sample size is greater than 30, then we use the z-test.

A good questionnaire can be of 25 to 30 questions and should be able to be administered within 30 min to keep the interest and attention of the participants intact.

We generally recommend a panel size of 30 respondents for in-depth interviews if the study includes similar segments within the population. We suggest a minimum sample size of 10, but in this case, population integrity in recruiting is critical.

Summary: 40 participants is an appropriate number for most quantitative studies, but there are cases where you can recruit fewer users. Share this article: The exact number of participants required for quantitative usability testing can vary.

Sampling ratio (sample size to population size): Generally speaking, the smaller the population, the larger the sampling ratio needed. For populations under 1,000, a minimum ratio of 30 percent (300 individuals) is advisable to ensure representativeness of the sample.

In general, three or four factors must be known or estimated to calculate sample size: (1) the effect size (usually the difference between 2 groups); (2) the population standard deviation (for continuous data); (3) the desired power of the experiment to detect the postulated effect; and (4) the significance level.

While there are no hard and fast rules around how many people you should involve in your research, some researchers estimate between 10 and 50 participants as being sufficient depending on your type of research and research question (Creswell & Creswell, 2018).

A sample size consisting of 50-100 respondents will be sufficient for obtaining comprehensive behavioral insights during emotion measurement.