Success is a journey, not a destination. —Arthur Ashe
The information provided in this chapter will assist the reader to:
Identify features of quantitative research, including manipulation, control, and randomization.
Understand basic quantitative research designs.
Explain how aspects of internal and external validity can impact outcomes of quantitative research.
Describe how reliability can influence outcomes of quantitative research.
“Quantitative research is a formal, objective, systematic process in which numerical data are used to obtain information about the world” (Burns & Grove, 2009, p. 22). Quantitative research designs are most often employed “to describe variables, examine relationships among variables, and determine cause-and-effect interactions between variables” (Burns & Grove, 2009, p. 22). In this chapter, some of the major quantitative research designs will be described and their advantages and disadvantages discussed. Of course, there are many more designs than those presented here, but beginning researchers should be able to find a design to fit their needs when starting the research process. Broad categories of research designs discussed here include experimental designs, quasi-experimental designs, and nonexperimental designs.
FEATURES OF QUANTITATIVE RESEARCH
Before choosing a quantitative research design, it is important to consider several features that can affect experimental rigor. These three concepts will be explored:
Manipulation merely means doing something to one or more variables in the study. A variable is anything that can vary or change and therefore can be measured. For example, if the researcher offers a group of patients with schizophrenia a daily program of self-care activities to determine whether their appearance can be improved, manipulation is provided in the form of daily self-care activities. Generally, any treatment or intervention offered to subjects in the hope that they will show improvement can be called manipulation. Changing the environment or the timing of an intervention can also be considered manipulation.
In other words, the researcher is manipulating one or more variables in connection with the subjects. In the foregoing example, the variable of self-care is being manipulated or given as treatment to determine whether it will have an effect on another variable, namely, the patient’s appearance.
Dependent and Independent Variables
It is important to understand the difference between variables in a quantitative study. The independent variable is the variable that is being manipulated, which could affect the outcome (or dependent variable). Conversely, the dependent variable is typically the variable being measured. In the previous example, the independent variable (self-care) is manipulated to determine the effect on the dependent variable (the patients’ appearance). The independent variable is sometimes called the experimental or treatment variable. The dependent variable (appearance) determines the effectiveness of the manipulation or treatment and ...