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As you know from reading the PhD Dissertation Handbook Research Methods, dissertation research must contribute to theory in a topic area: A dissertation research problem is a GAP in recent research (usually in the past five years) in a topic area that can be addressed by a study that will contribute to knowledge and theory in the area. The ways that quantitative research can make a theory contribution are limited only by imagination and knowledge of design, statistics, and literature in a topic area. One very effective strategy for contributing to theory in a quantitative study is to identify variables that the literature on a topic suggests may cause an outcome or mediate or moderate a known relationship between a cause and an effect. A research problem for a quantitative study will usually be a statement describing something we do not know about the relationships among constructs in a topic area.
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Here is a fictitious example: Say your review of the literature shows that we know that smiling causes happiness. It also shows that there is disagreement among researchers and theorists in these areas: a. on how smiling causes happiness; b. under what conditions and for what type of people smiling causes happiness; and, c. what else causes happiness Your research can contribute to theory on the relationship between smiling and happiness by addressing a) or b). Addressing c) is a completely different matter. c) involves identifying constructs that also cause happiness. You would be unlikely to choose this option, because it is not directly related to the smiling/happiness relationship. It involves you in the huge project of developing a general theory of happiness, which is too ambitious for a dissertation study. If, however, your literature review uncovers a theory of happiness that predicts that smiling causes happiness but no one has done a controlled study to see if it in fact does, then you could conduct a study to see if smiling causes happiness that would contribute to theory. It is important to understand that a study that looks to see if one variable causes an effect on another does not necessarily contribute to theory. For example, simply looking to see if a treatment works (causes an effect, an improvement, is more effective than a placebo) does not contribute to theory, unless you are specifically testing an untested cause and effect relationship claim made in a theory, as in the happiness theory example. For example, if a theory claims that based on what is known about how Y develops in childhood, treatment or intervention X should produce more Y, you are testing a theory and so contributing to it by providing empirical evidence for or against a theory claim. Without the context of a theory that gives a reason why X causes Y, you are conducting an applied study. Back to studying the smiling/happiness relationship. Here is how your study could add to our understanding of the relationship.
Your study could:
1. Address phenomena that mediate the smiling/happiness relationship. Our knowledge of human biology tells us smiling cannot directly cause happiness. Smiling must be the beginning of a causal chain of events ending with happiness. Your literature review would identify plausible links, and your study would examine if they are in fact present when people smile and report feeling happy. Your study would contribute to theory on how smiling causes happiness.
2. Address constructs that moderate the smiling/happiness relationship. Your literature review would show you that smiling only leads to happiness under certain conditions (e.g., when people are in a calm mood and not severely depressed). Your review of the literature would suggest plausible candidates for the conditions under which the relationship holds. Your study would contribute to theory on how smiling causes happiness by telling us something about the conditions under which the smiling/happiness relationship holds.
As you may gather from the readings for this activity, scientists view the world as a vast interconnected network of mediated and moderated cause and effect relationships. These relationships can be extremely complex. A only mediates X and Y under condition P. Under condition Q, B mediates X and Y. B is a moderator in some contexts, a mediator in others. Etc. No one ever said life was simple!
