ROUTE #1: Getting Started
ROUTE #1: Chapter-by-Chapter

Choose your sampling strategy and sampling technique

Once you understand the basic principles and characteristics of sampling, you need to start thinking about the overall sampling strategy that you will use to collect the data needed for your dissertation. In other words, you need to identify: (a) the units you will be studying (i.e., whether they people, objects, cases, pieces of data, etc.), and their characteristics; (b) the sampling technique that you will use to select the units that you will include in your sample (i.e., whether a probability or non-probability sampling technique, and the specific technique being used; e.g., a simple random sample as your choice of probability sampling technique); and (c) the practical aspects of selecting the units using this sampling technique (e.g., creating rules for randomly sampling participants within an overt, structured observation).

When you choose your sampling strategy, you also need to take into account: (a) the consistency between your sampling strategy, research design and research methods; (b) your chosen route, and the approach you have adopted within that route; and related to this; and finally, (c) the practicalities of choosing such a sampling strategy for your dissertation (e.g., what time you have available, what access you have, etc.).

The consistency of your sampling strategy with your research strategy

One of the major aims of quantitative research (i.e., quantitative dissertations) is the desire to make generalisations (i.e., statistical inferences) from the sample you are studying to the broader population you are interested in (e.g., from the 300 students in your sample to the 15,000 students at your university). To make such generalisations, you need to make sure that the units you are studying in your sample (e.g., statistical inferences, the 300 students) are representative of this broader population (i.e., representative in terms of the characteristics of the units, such as age, gender, educational background, etc.). The more representative your sample is of the broader population, the greater the external validity (i.e., generalizability) of your findings (NOTE: We discuss external validity further in STEP FIVE: Research quality). To achieve such representativeness, the units that end up in your sample should be drawn at random from the population, which is a major aspect of probability sampling techniques. However, this is not always possible, such that non-probability sampling techniques have to be used instead, reducing the potential representativeness of your sample, and limiting the external validity of your findings.

Added to this, you have to consider the consistency of your sampling strategy in terms of your research strategy. For example, if you are following an experimental research design, participants need to be randomly assigned to groups using a probability sampling technique (e.g., a simple random sample). However, if this is not possible, you will only be able to follow a quasi-experimental research design, which lacks some of the explanatory power of experimental research designs. Therefore, when considering the sampling strategy you want to follow, you need to make sure that it is consistent with your research strategy. If, as the above example illustrates, this is not possible, you may not only have to change your desired sampling technique (e.g., from a probability sampling one to a non-probability sampling one), but also go back and change an aspect of your research strategy (e.g., a change of your research design from an experimental one to a quasi-experimental one). When such changes have to be made, go back to the relevant section within STAGE SIX: Research strategy, and work back through the steps. For example, if you have to change your research design from an experimental to a quasi-experimental one, you would need to read up on quasi-experimental research designs and how they are different from experimental research designs. This is important because as you work your way through STAGE SIX: Research strategy, you find that many things are influenced by such changes, especially factors relating to research quality, which we discuss in STEP FIVE: Research quality.

Your chosen route and approach

Since you are taking on a Route #1: Replication-based dissertation, the main journal article you are interested in may be able to give you some idea of the sampling strategy you could follow in your dissertation. However, the extent to which this is the case will vary depending on the route you adopt, and the approach within that route. Route A: Duplication, Route B: Generalisation and Route C: Extension are discussed in turn:

The practicalities of your chosen sampling strategy

At the end of the day, the sampling strategy that you select is something very practical. For example:

All of these types of practicalities need to be taken into account when choosing your sampling strategy.

Consider the practical aspects of your dissertation, and the implications that these may have for your sampling strategy

There are many ideals when it comes to setting a research strategy for your dissertation, and the sampling strategy is no different. As you will have noticed in the previous sections, such ideals may be based on (a) the sampling strategy adopted in the main journal article, (b) your chosen route, and the approach within that route, and (c) the sampling technique that is consistent with your chosen research design and research method.

However, it is often not possible to adhere to such ideals, especially at the undergraduate and master's level, for a variety of reasons. For example, probability sampling techniques require that you can attain a list of the population you are studying from which you can draw your sample. However, even if a list is readily available, it may be challenging to gain access to that list. The list may be protected by privacy policies or require a lengthy process to attain permissions. There may be no single list detailing the population you are interested in. As a result, it may be difficult and time consuming to bring together numerous sub-lists to create a final list from which you want to select your sample. As an undergraduate and master's level dissertation student, you may simply not have sufficient time to do this. At the same time, many lists will not be in the public domain and their purchase may be expensive; at least in terms of the research funds of a typical undergraduate or master's level dissertation student.

These and other issues highlight just some of the problems that you can face when devising the ideal sampling strategy for your dissertation. As a result, you often have to be pragmatic when setting your sampling strategy, devising the best sampling strategy that you can based on your available resources, whilst acknowledging in your write up (i.e., the Sampling Strategy section of your Chapter Three: Research Strategy) the weaknesses of your chosen approach.

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