ROUTE #1: Process
ROUTE #1: Chapter-by-Chapter

Testing the generalizability of a study

As discussed in Route B: Generalisation, one of the main goals of quantitative research is generalisation; that is, testing to see whether the findings from the study you are interested in replicating hold across a range of populations, settings/contexts, treatments and time. But the justification for generalisation goes further than a basic desire to see how far a study's findings hold. It is a philosophical, theoretical and practical question:

Building the construct validity and reliability of a measurement procedure

As discussed earlier, quantitative research involves the study of constructs and the measurement of variables. The study you choose to replicate will involve such constructs and variables, irrespective of the type of replication-based dissertation you take on.

To briefly recap, constructs are mental abstractions that we use to express the ideas (e.g., ageism, poverty, air pollution), people (e.g., obesity, morbidity, age, etc.), organisations (e.g., service quality, firm survival, outsourcing, etc.), events (e.g., famine, urban regeneration, Jihad, etc.), and/or objects/things (e.g., trees, stem cells, hurricanes, etc.) that we are interested in. We often refer to constructs as mental abstractions because seldom are constructs directly observable (e.g., we cannot directly observe depression, even though we may associate depression with signs such as a person that often cries, engages in self-harm, has mood swings, etc.). Instead, we use variables to operationalize (i.e., measure) the constructs we are interested in (e.g., we may measure the construct, obesity, using the variable, Body Mass Index (BMI)).

When we examine a construct in a study, we choose one of a number of possible ways to measure that construct. For example, we may choose to use questionnaire items, structured interview questions, and so forth. These questionnaire items or structured interview questions are part of the measurement procedure. This measurement procedure should provide an accurate representation of the construct it is measuring if it is to be considered valid. For example, if we want to measure the construct, intelligence, we need to have a measurement procedure that accurately measures a person's intelligence. Since there are many ways of thinking about intelligence (e.g., IQ, emotional intelligence, etc.), this can make it difficult to come up with a measurement procedure that has strong construct validity.


Specific justifications for replication-based dissertations

In the previous section, we highlighted three of the common justifications for replication-based dissertations, but there are actually a wide range of more specific reasons why a particular study should be replicated. If you choose to pursue this route in your dissertation, understanding these specific reasons in the context of the study you want to replicate will be very important. Whilst we do not go into detail now, we provide the explanation needed to identify many of these more specific justifications for replication-based dissertations within the Lærd Dissertation site. At this point, it is worth more broadly determining whether a replication-based dissertation is right for you, which we do next, in STEP THREE.

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