Are you in the stage of putting your research data into different treatment groups? If yes, then you must have an idea of what random assignment in experiments is. Ohh, it is sad to hear that you do not know about this important phase in research before analysing the data. Nevertheless, do not worry because today’s article is all about discussing the randomisation technique of placing data into different treatment groups. First, I will discuss the random assignment in experiments and then shed some light on its purpose. In the last, I will talk about some techniques for doing randomisation. So, let’s formally enter into today’s discussion by answering the question below:
What is a random assignment in experiments?
The word random here explains the whole phenomenon very well. However, in experimental research design, random assignment is the practice of placing participants from your population into different treatment groups using the technique of randomisation. This type of research method is mostly in psychology, where there is potential fear of bias in the data. So, to save the data from bias, you use the technique of random assignment.
Why is random assignment important? It is an important part of control in experimental research because it helps strengthen the internal validity of an experiment. It is also important in the way that random assignment in experiments helps you make sure that the treatment groups do not differ at the start of the experiment. It is important to note here that random sampling is different from random assignment. Therefore, hiring an assignment writing service UK becomes important.
What is the purpose of the random assignment?
After reading the information above, you now have a pretty good idea of random assignment in experiments. You have also learned the importance of using this method in research data analysis. Now, let’s discuss the purpose of random assignment. A list of the purposes in the form of pointers is as follows:
- It allows the participants in the experimental research design to be exposed to the independent variable.
- Random assignment ensures that each participant in the sample has an equal chance of being selected in the research process.
- It eliminates the placebo effect from your research.
- It reduces the researcher bias in the research
Top techniques to do random assignment
Random assignment has been frequently used in psychology and social science research. It has its uses in clinical trials and other biological experiments too. It prevents selection bias and maintains the internal validity of the experiment. However, you still do not know how to perform the random assignment in experiments. Hence, a brief description of the top techniques is as follows:
1. Simple random assignment
The first technique of random assignment is single randomisation. This technique is based on a single sequence. It means you randomly assign a participant to a particular group in a single turn and then make another assignment in the next round. So, in this way, a sequence generates, and the researcher follows that sequence and puts the participants in a specific group.
For example, you use a flip coin to place the participants into two different groups called treatment and control. Now, you assign one side of the coin, e.g., the head side, to the control group and the other side to the treatment group. So, upon flipping the coin, if you get a head, you put the participant in the control group and vice versa. Hence, this is the technique of simple random assignment.
2. Block random assignments in experiments
This randomisation method is used to randomise participants into groups that result in equal sample sizes. The block random assignment is used to ensure a balance in sample size across the formulated groups. In this randomisation technique, the blocks are small and predetermined. The number of groups is always even in this technique, i.e., 4 and 6. After this, you divide the groups into two groups, i.e., control and treatment.
For example, the possible groups within each population sample are A and B. The block randomisation tells you that groups should be in even numbers. So, the group can be in the form of AABB, BBAA, ABAB, BABA, ABBA, or BAAB.
3. Stratified randomisation
Stratified randomisation is the process of allocating people to treatment groups at random. This allocation is based on a set of predetermined and measurable parameters known as strata. Treatment groups are assigned at random to each stratum. Now, in this technique, the researcher decides on the fate of the participant, whether it will go into the control group or the treatment group.
Moreover, this randomisation is done by generating a separate block for each stratum. The benefit of this technique is that it controls the influence of covariates that jeopardise the conclusion of the research. Hence, it is the third technique most commonly used.
4. Unequal random assignment in experiments
A potential failure of simple randomisation is that it may result in the imbalance of important participants among different groups. So, many researchers have recommended unequal randomisation as a solution to this problem. In this technique, you assign a new participant to each group if needed. The basis of the introduction of this new participant is the imbalance that exists in the groups due to other techniques. You do so by the specific groups and the previous assignment of the participants to the groups.
It is important to note that the acceptable ratio for this unequal randomisation is 2:1, 3:1, and 4:1. This method of random assignment in experiments is useful for rare events, adverse events, and emerging clinical techniques. Hence, it is a powerful method which reduces the imbalance between the groups.
Random assignment in experiments is all about allocating random participants to a group. The primary purpose of this method is to reduce selection bias, which ultimately affects the validity of the research. So, you must study all the techniques mentioned above and ensure the use of these techniques in your research. Read the above and make your research bias-free.
You might also like to read about the steps to convert academic research into industrial research.