The strategy uses for this study is going to be quantitative. In quantitative research, your aim is to determine the relationship between one thing (an independent variable) and another (a dependent or outcome variable) in a population. Quantitative research designs are either descriptive (subjects usually measured once) or experimental (subjects measured before and after treatment). A descriptive study establishes only associations between variables. An experiment establishes causality.
For an accurate estimate of the relationship between variables, a descriptive study usually needs a sample of hundreds or even thousands of subjects; an experiment, especially a crossover, may need only tens of subjects. The estimate of the relationship is less likely to be biased if you have a high participation rate in a sample selected randomly from a population. In experiments, bias is also less likely if subjects are randomly assigned to treatments, and if subjects and researchers are blind to the identity of the treatments.
In all studies, subject characteristics can affect the relationship you are investigating. Limit their effect either by using a less heterogeneous sample of subjects or preferably by measuring the characteristics and including them in the analysis. In an experiment, try to measure variables that might explain the mechanism of the treatment. In an unblinded experiment, such variables can help define the magnitude of any placebo effect. Quantitative research is used to measure how many people feel think or act in a particular way. These surveys tend to include large samples – anything from 50 to any number of interviews. Structured questionnaires are usually used incorporating mainly closed questions – questions with set responses. There are various vehicles used for collecting quantitative information but the most common are on-street or telephone interviews.
Quantitative research is all about quantifying relationships between variables. Variables are things like weight, performance, time, and treatment. You measure variables on a sample of subjects, which can be tissues, cells, animals, or humans. You express the relationship between variable using effect statistics, such as correlations, relative frequencies, or differences between means. I deal with these statistics and other aspects of analysis elsewhere at this site. In this article, I focus on the design of quantitative research. First I describe the types of study you can use. Next, I discuss how the nature of the sample affects your ability to make statements about the relationship in the population. I then deal with various ways to work out the size of the sample. Finally, I advise about the kinds of variable you need to measure.
Studies aimed at quantifying relationships are of two types: descriptive and experimental (Table 1). In a descriptive study, no attempt is made to change behavior or conditions – you measure things as they are. In an experimental study, you take measurements, try some sort of intervention, then take measurements again to see what happened.
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