Non-Probability Sampling

• Non-probability sampling is a sampling technique where the samples are gathered in a process that does not give all the individuals in the population equal chances of being selected. In any form of research, true random sampling is always difficult to achieve. Most researchers are bounded by time, money and workforce and because of these limitations, it is almost impossible to randomly sample the entire population and it is often necessary to employ another sampling technique, the non-probability sampling technique. In contrast with probability sampling, non-probability sample is not a product of a randomized selection processes. Subjects in a non-probability sample are usually selected on the basis of their accessibility or by the purposive personal judgment of the researcher. 
• The downside of the non-probablity sampling method is that an unknown proportion of the entire population was not sampled. This entails that the sample may or may not represent the entire population accurately. Therefore, the results of the research cannot be used in generalizations pertaining to the entire population.
• The difference between nonprobability and probability sampling is that nonprobability sampling does not involve random selection and probability sampling does. Does that mean that nonprobability samples aren't representative of the population? Not necessarily. But it does mean that nonprobability samples cannot depend upon the rationale of probability theory. At least with a probabilistic sample, we know the odds or probability that we have represented the population well. We are able to estimate confidence intervals for the statistic. With nonprobability samples, we may or may not represent the population well, and it will often be hard for us to know how well we've done so. In general, researchers prefer probabilistic or random sampling methods over nonprobabilistic ones, and consider them to be more accurate and rigorous. However, in applied social research there may be circumstances where it is not feasible, practical or theoretically sensible to do random sampling. Here, we consider a wide range of nonprobabilistic alternatives. We can divide nonprobability sampling methods into two broad types: accidental or purposive. Most sampling methods are purposive in nature because we usually approach the sampling problem with a specific plan in mind. The most important distinctions among these types of sampling methods are the ones between the different types of purposive sampling approaches.
• Sampling is the use of a subset of the population to represent the whole population or to inform about (social) processes that are meaningful beyond the particular cases, individuals or sites studied. Probability sampling, or random sampling, is a sampling technique in which the probability of getting any particular sample may be calculated. Nonprobability sampling does not meet this criterion and, as any methodological decision, should adjust to the research question that one envisages to answer. Nonprobability sampling techniques cannot be used to infer from the sample to the general population in statistical terms and thus answer "how many"-related research questions. Thus, one cannot say the same on the basis of a nonprobability sample than on the basis of a probability sample. The grounds for drawing generalizations (e.g., propose new theory, propose policy) from studies based on nonprobability samples are based on the notion of "theoretical saturation" and "analytical generalization" (Yin, 2014) instead of on statistical generalization. Researchers working with the notion of purposive sampling assert that while probability methods are suitable for large-scale studies concerned with representativeness, non-probability approaches are more suitable for in-depth qualitative research in which the focus is often to understand complex social phenomena (e.g., Marshall 1996; Small 2009). One of the advantages of nonprobability sampling is its lower cost compared to probability sampling. Moreover, the in-depth analysis of a small-N purposive sample or a case study enables the "discovery" and identification of patterns and causal mechanisms that do not draw time and context-free assumptions. From the point of view of the quantitative and statistical way of doing research, though, these assertions raise some questions —how can one understand a complex social phenomenon by drawing only the most convenient expressions of that phenomenon into consideration? What assumption about homogeneity in the world must one make to justify such assertions? Alas, the consideration that research can only be based in statistical inference focuses on the problems of bias linked to nonprobability sampling and acknowledges only one situation in which a non-probability sample can be appropriate —if one is interested only in the specific cases studied (for example, if one is interested in the Battle of Gettysburg), one does not need to draw a probability sample from similar cases (Lucas 2014a).

Types of Non-Probability Sampling

Convenience Sampling

Convenience sampling is probably the most common of all sampling techniques. With convenience sampling, the samples are selected because they are accessible to the researcher. Subjects are chosen simply because they are easy to recruit. This technique is considered easiest, cheapest and least time consuming.

Consecutive Sampling

Consecutive sampling is very similar to convenience sampling except that it seeks to include ALL accessible subjects as part of the sample. This non-probability sampling technique can be considered as the best of all non-probability samples because it includes all subjects that are available that makes the sample a better representation of the entire population.

Quota Sampling

Quota sampling is a non-probability sampling technique wherein the researcher ensures equal or proportionate representation of subjects depending on which trait is considered as basis of the quota.

For example, if basis of the quota is college year level and the researcher needs equal representation, with a sample size of 100, he must select 25 1st year students, another 25 2nd year students, 25 3rd year and 25 4th year students. The bases of the quota are usually age, gender, education, race, religion and socioeconomic status.

Judgmental Sampling

Judgmental sampling is more commonly known as purposive sampling. In this type of sampling, subjects are chosen to be part of the sample with a specific purpose in mind. With judgmental sampling, the researcher believes that some subjects are more fit for the research compared to other individuals. This is the reason why they are purposively chosen as subjects.

Snowball Sampling

Snowball sampling is usually done when there is a very small population size. In this type of sampling, the researcher asks the initial subject to identify another potential subject who also meets the criteria of the research. The downside of using a snowball sample is that it is hardly representative of the population.

When to Use Non-Probability Sampling

This type of sampling can be used when demonstrating that a particular trait exists in the population.

It can also be used when the researcher aims to do a qualitative, pilot or exploratory study.

It can be used when randomization is impossible like when the population is almost limitless.

It can be used when the research does not aim to generate results that will be used to create generalizations pertaining to the entire population.

It is also useful when the researcher has limited budget, time and workforce.

This technique can also be used in an initial study which will be carried out again using a randomized, probability sampling.

Article Credit : explorable.com

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What is Meta-theories?

• A metatheory or meta-theory is a theory whose subject matter is some theory. All fields of research share some meta-theory, regardless whether this is explicit or correct. In a more restricted and specific sense, in mathematics and mathematical logic, metatheory means a mathematical theory about another mathematical theory. Any physical theory is always provisional, in the sense that it is only a hypothesis; you can never prove it. No matter how many times the results of experiments agree with some theory, you can never be sure that the next time the result will not contradict the theory. On the other hand, you can disprove a theory by finding even a single observation that disagrees with the predictions of the theory.      ”
• Meta-theoretical investigations are generally part of philosophy of science. Also a metatheory is an object of concern to the area in which the individual theory is conceived.
• Metatheory, which deals with methods of evaluating theories, has traditionally been the province of philosophers of science, although psychologists implicitly use metatheories whenever they evaluate theories. The original figure below is a taxonomy of metatheories. Click on any approach to knowledge below the figure to learn more about it.
• A metatheory is a set of interlocking rules, principles, or a story (narrative), that both describes and prescribes what is acceptable and unacceptable as theory - the means of conceptual exploration - in a scientific discipline. For example, the prevailing metatheory might prescribe that change of form (transformational change) is, or is not, a legitimate way of understanding developmental change. If the prevailing metatheory accepted the legitimacy of transformational change, then theories of development would include some type of stage concept, because "stage" is the theoretical concept that is used to describe transformational change.
•      A methodology is a set of interlocking rules, principles, or a story, that describes and prescribes the nature of acceptable methods -- the means of observational exploration - in a scientific discipline. For example, the prevailing methodology might prescribe that the assessment of sequences is, or is not, critical to understanding developmental change. If deemed critical to methodology, sequential assessment methods would assume a central place as a tool of empirical inquiry.
•      Metatheory and methodology are closely interrelated and intertwined. Metatheory presents a vision of the nature of the world and the objects of that world (e.g., do you accept a picture of persons as "active agents" "constructing" their known world, or as "recoding devices" that "process" information). Methodology presents a vision of the tools we can use to explore that world.