Selection of Sample in Qualitative, Quantitative, and Mixed Method
Introduction
Sampling is
a critical, often overlooked aspect of the research process. The importance of
sampling extends to the ability to draw accurate inferences, and it is an
integral part of qualitative guidelines across research methods. Sampling
considerations are important in quantitative and qualitative research when
considering a target population and when drawing a sample that will either
allow us to generalize (i.e., quantitatively) or go into sufficient depth
(i.e., qualitatively). While quantitative research is generally concerned with
probability-based approaches, qualitative research typically uses
nonprobability purposeful sampling approaches. Scholars generally focus on two
major sampling topics: sampling strategies and sample sizes. Or simply, researchers
should think about who to include and how many; both of these concerns are key.
Mixed methods studies have both qualitative and quantitative sampling
considerations. However, mixed methods studies also have unique considerations
based on the relationship of quantitative and qualitative research within the
study.
Sampling in
Qualitative Research
Sampling in qualitative research may be divided into two major areas: overall sampling strategies and issues around sample size. Sampling strategies refers to the process of sampling and how to design a sampling. Qualitative sampling typically follows a nonprobability-based approach, such as purposive or purposeful sampling where participants or other units of analysis are selected intentionally for their ability to provide information to address research questions.
Sample size refers to how many participants or other units are needed to address research questions. The methodological literature about sampling tends to fall into these two broad categories, though some articles, chapters, and books cover both concepts. Others have connected sampling to the type of qualitative design that is employed.
Additionally, researchers might
consider discipline-specific sampling issues as much research does tend to
operate within disciplinary views and constraints. Scholars in many disciplines
have examined sampling around specific topics, research problems, or
disciplines and provide guidance to making sampling decisions, such as
appropriate strategies and sample size.
Sampling in
Quantitative Research
Quantitative researchers are often interested in being able to make generalizations about groups larger than their study samples. While there are certain instances when quantitative researchers rely on nonprobability samples, quantitative researchers tend to rely on probability sampling techniques. The goals and techniques associated with probability samples differ from those of nonprobability samples. Unlike nonprobability sampling, probability sampling refers to sampling techniques for which a person’s (or event’s) likelihood of being selected for membership in the sample is known.
Researchers who use
probability sampling techniques are aiming to identify a representative sample
from which to collect data. Obtaining a representative sample is important in
probability sampling because a key goal of studies that rely on probability
samples is generalizability. In order to achieve generalizability, a core
principle of probability sampling is that all elements in the researcher’s
target population have an equal chance of being selected for inclusion in the
study. In research, this is the principle of random selection. Random selection
is a mathematical process that we won’t go into too much depth about here, but
if you have taken or plan to take a statistics course, you’ll learn more about
it there. If a researcher uses random selection techniques to draw a sample, he
or she will be able to estimate how closely the sample represents the larger
population from which it was drawn by estimating the sampling error. Sampling
error is a statistical calculation of the difference between results from a
sample and the actual parameters of a population.
Sampling in Mixed Research
Mixed
methods studies have both qualitative and quantitative sampling considerations.
It combines quantitative and qualitative approaches by including both
qualitative and quantitative data in a single study.
Advantages of Mixed Research
- Weaknesses in one method can be compensated for by strength in another.
- Can account for a broad range of variables questions and hypotheses.
- Cover holes in the theory.
- Approach a topic from more than one point of view.
Lecture on Selection of Sample in Qualitative, Quantitative, and Mixed Method
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