Experimental Versus Nonexperimental Research
When conducting experimental research , the researcher sets up the study to evaluate an experimental drug, treatment, or intervention. This type of research is a randomized control trial (RCT) . Some patients receive the experimental drug, treatment, or procedure, and the other group does not. Randomization involves something similar to a coin toss (see Figure 4.3).
Example: Randomization Control Study
In randomized control trials, the control group is the group in which no experimentation occurs. The control group receives customary and routine treatment. The experimental group is where the independent variable is manipulated. In randomized control research designs, one group of patients will receive the experimental drug, treatment, or procedure, and the other group of patients will receive customary treatment. Randomization is like flipping a coin (see Figure 4.3). Heads the patient is in the group that receives the experimental intervention, tails the patient receives the customary treatment. Another research scenario could be the study of a new medication. In this case, it could be the dose of the medication that is different among the groups. This allows the researchers to evaluate the effects of dosage on the patients in different groups. Table 4.1 provides a visual example of manipulation, control, and randomization for experimental research.
Manipulation, Control, and Experimentation
|Patient A(Manipulation)||Lisinopril||20 mg||ManipulationManipulation of dosage. ↑40 mg—independent variable|
|Patient B(Tails: Control Group)||Lisinopril||20 mg||ControlControl Group: Randomization. Coin toss. Patient is randomly placed in the control group of the study, receiving customary treatment.. Nothing is changed.|
|Patient C(Heads: Experimental Group)||Lisinopril||20 mg||ExperimentationExperimental Group: Randomization. Coin toss. Heads: New medication; patient started on propranolol 10 mg daily.|
All RCTs are experimental. The research design specifies the study sample that will be selected to participate in the trial or study. Once the population is defined, the participant is randomized into either the control group or the experimental group. Different methods are used to randomize the participants. Experimental designs can establish causation. A high degree of internal validity can be obtained through similar control and experimental groups. In research, one cannot receive less than the usual customary treatment. The participant in the experimental arm can be subjected to risk by not receiving the usual and customary treatment.
A good experiment minimizes the variability of the evaluation and provides unbiased evaluation of the intervention by avoiding confounding from other factors, which are known and unknown. Randomization ensures that each patient has an equal chance of receiving any of the treatments under study. (Suresh, 2011, para. 2)
There are several different methods the research investigator can use for randomization. Methods of randomization include basic randomization, which is based off of a single event, such as flipping a coin or rolling dice. Some methods are more complicated, such as opening an envelope or placing a phone call to receive a control or experimental group assignment for the patient. These different types of randomization may not always work because there may be too many independent variables. The study must conform to the rules and regulations set by the Code of Federal Regulations to remain ethical.
A quasi-experimental study is able to identify why certain things happen. A quasi-experimental study does not use any form of randomization but looks for a causal relationship between receiving a treatment and not receiving a treatment. With the absence of randomization, the study can no longer be considered experimental. Quasi-experimental research designs identify treatment groups and comparison groups (see Figure 4.4). Because there is no randomization, selection may be based on similar characteristics or similar comorbidities. Extraneous variables may be responsible for jeopardizing internal validity . Extraneous variables are variables that are not foreseen. The researcher is not aware of extraneous variables when designing a research study.
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