Experimental Research
In experimental research, the researcher is an active agent rather than a passive observer. To do an experimental research, the researcher has to follow these principles such as
1. Manipulation
2. Control
3. Randomization
It means the researcher intervenes something in the group and analyze the outcome. In other words, the researcher varies the independent variable by administering an intervention or treatment and analyzes its effects on the dependent variable. For example, the researcher analyzes the level of knowledge (dependent variable) before and after video teaching programme (intervention).
Control group refers to a group of participants whose performance on dependent variable is used as a basis for evaluating the performance of the experimental group (a group which receives intervention) on the same dependent variable. The researcher keeps the control group (a group with no intervention or administers an alternative or false intervention such as placebo) parallel to experimental group. For example, to evaluate the effectiveness of nutritional supplements, the researcher divides the newborns into two groups with different mode of strategies.
Strategy I: A group of newborns receiving nutritional supplements daily (experimental group) and other group without any nutritional supplements (control group).
Strategy II: A group of newborns receiving nutritional supplements daily (experimental group) and other group with alternatives to nutritional supplements such as glucose powder called a group with placebo intervention (control group).
Randomization means the researcher randomly select the participants in the study without any bias. Through randomization, the every participant gets an equal chance to participate in the study. The methods of randomization may vary from flipping a coin to computerized randomization method.
Experimental designs
Basic Designs
The researcher assigns the subjects randomly into experimental and control group, intervenes the intervention in the experimental group and collects the data after intervention from experimental and control group. This is also called as after only or post test only design. In another way, the researcher collects the information from experimental and control group before and after intervention is called as before-after design or pretest-post test design.
Factorial design
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| Factorial Design |
In factorial design, the researchers manipulate two or more variables together on the study subjects and evaluate the main effects and also interaction effects. Here, the subjects are assigned at random to a combination of treatments. The term cell represents in a schematic diagram as a box. The independent variables are referred to as factors. Each factor is exposing in different levels. For example, a study to assess the effectiveness of supplementary feeding versus normal feeding among toddlers on weight gain. Here, the researcher designs the study on 2×2 table with two factors such as type of feeding A (Supplementary feeding (A1) and normal feeding (A2) and frequency of feeding B one time/day (B1) and two times per day (B2). The researchers assign the toddlers randomly to one of the cells, which consist of combination of treatments. The results will show the best mode of feeding and also the interaction effects resulting from the combination of treatment methods.
Repeated measures design/ Cross over design
The researchers intervene two or more interventions among the same subjects called within subjects design or cross over design. It involves the exposure of the same study participants to more than one treatment. The study subjects are randomly assigned to receive different ordering of treatment. For example, to compare the effects of auditory and tactile stimulation on infants, some subjects would like to randomly assign to receive auditory stimulation first and others would receive tactile stimulation first with the subjects serving as their own control group. It prevents participant bias by achieving possible equivalence among subjects exposed to different conditions. There is an expected disadvantage of carryover effects of first treatment among study participants. When the researcher introduces two or more treatments and intervenes the treatments in the randomized order is called as experimental repeated measures design.
Clinical trials
The researcher evaluates the effectiveness of new treatment through a randomized clinical trial. It involves the testing of a clinical treatment, random assignment of subjects to experimental and control groups and assesses the effectiveness of treatment. Clinical trials can be done using before – after or after only design.
Advantages of experiments
These are the most powerful designs for testing hypothesis of cause and effect relationships. It also meets the criteria of causality, by Lazarsfield (1955).
1. A cause must precede an effect in time. For example, to test the hypothesis- smoking causes lung cancer; subjects should not have developed cancer before exposure to smoking.
2. There must be an empirical relationship between the presumed cause and effect. For example, in case of smoking and lung cancer, the researcher should collect the evidences regarding higher incidence of lung cancer is directly related to occurrence of smoking.
3. The relationship of presumed cause and effect should not affect by a third variable. For example, a relationship between smoking and lung cancer might reflect an underlying causal relationship between prolonged dust exposure and lung cancer.
Through manipulation, presence of control groups and randomization, an alternative explanation to a causal interpretation can be ruled out.
Disadvantages of experiments
All variables can not be manipulated such as race, ethnicity and history of diseases.
There are many variables, which can not be manipulated ethically. For example, withdrawal of vaccines from control group to test the effectiveness of vaccines in experimental and control group.
Hawthorne effect- Awareness of being in a study may alter the participant’s behavior, which affects the study results.
Double hawthorne effect- Those who administer the treatment know the subjects who are in experimental and control group; alters the study results. In a double blind experiment, neither the subjects nor those administering the treatment know who is in the experimental or control group; are so powerful.
