Module Components

• Learning Activities

Topics

• Foundations of Research
• Time
• Research Designs
• Theory in Research
• Module 2 Self-Review

NRSG 790 - Methods for Research and Evidence-Based Practice

Module 2: Research Overview and Design

Research Design

Research design provides the glue that holds the research project together. A design is used to structure the research, to show how all of the major parts of the research project -- the samples or groups, measures, treatments or programs, and methods of assignment -- work together to try to address the central research questions.

Types of Designs

What are the different major types of research designs? We can classify designs into a simple threefold classification:

1. First, does the design use random assignment to groups? Random assignment is not the same thing as random selection of a sample from a population.  If random assignment is used, we call the design a randomized experiment or true experiment. If random assignment is not used, then we have to ask a second question:
2. Does the design use either multiple groups or multiple waves of measurement? If the answer is yes, we would label it a quasi-experimental design. If no, we would call it a non-experimental design or observational.

A randomized experiment generally is the strongest of the three designs when your interest is in establishing a cause-effect relationship. A non-experiment is generally the weakest in this respect. When we say that the non-experiment is the weakest with respect to internal validity, it means that it isn't a particularly good method for assessing the cause-effect relationship that you think might exist between a program and its outcomes.

• Experimental designs are often touted as the most "rigorous" of all research designs or, as the "gold standard" against which all other designs are judged. In one sense, they probably are. If you can implement an experimental design well (and that is a big "if" indeed), then the validity is strengthened
• Experimental design is probably the strongest design with respect to internal validity. Why? Recall that internal validity is at the center of all causal or cause-effect inferences. When you want to determine whether some program or treatment causes some outcome or outcomes to occur, then you are interested in having strong internal validity.

A quasi-experimental design is one that looks a bit like an experimental design but lacks the key ingredient -- random assignment. With respect to internal validity, they often appear to be inferior to randomized experiments. But there is something compelling about these designs; taken as a group, they are easily more frequently implemented than their randomized cousins.