random homework assignment
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template21.docxThe Importance of Random Assignment
Dear student,
Thank you for your questions regarding the importance of participant randomization. There are three main reasons why researchers randomly assigned participants to experimental conditions. The first reason is that it is intended to provide a safeguard against the possibility of the researchers’ subconsciously letting their opinions or preferences influence which sampling units will receive a given treatment (Gigerenzer, 1989). In other words, randomizing participants will help eliminate influence from the researchers to achieve favorable results. As you can imagine, it takes an incredible amount of time, money and hard work to develop research topics and execute experiments. When so much is riding on the results, it’s incredibly important that the results are authentic.
The second reason researchers randomly assign participants is that it distributes the characteristics of the sampling units over the experiment and control conditions in a way that should not bias the outcome of the experiment (Kirk, 2000) In other words, everyone participating in the experiment will be able to contribute to the experiment in their own way. Each participant has their own unique background which will generate better results and will lower the chances of results being populated due to a common characteristic among participants.
The third reason participants are randomly assigned to experiments is that random assignment permits the computation of statistics that require particular characteristics of the data. It provides a mechanism to derive probabilistic properties of estimates based on the normal distribution of data curve. In other word, randomization of participants helps the process of developing statistics that you can compare to other data. Being able to show your findings in a statistical way helps interpret your findings for others to read.
These three reasons aren’t the only reasons random assignment is important but they are very important and contribute to unbiased, statistically significant research. Even if you use a large enough sample, you still have to account for researcher bias.
There are two different types of randomization, random sampling and random assignment. Say there are 1,000 people willing to participate in your study. If you randomly pick 100 out of the 1,000 this would be considered your random sample. If you choose 100 participants and you randomly assign 50 of them to take the treatment and 50 of them are taking a placebo than this is considered random assignment. In other words, random sampling is the people you randomly choose to partake in your study and random assignment is the people who are randomly choose to be part of the experimental group vs the placebo group.
Random selection is related to sampling. Therefore it is related to the external validity of your results. After all, we would randomly sample so that our research participants better represent the larger group from which they're drawn. Random assignment is related to design. In fact, when we randomly assign participants to treatments we have, by definition, an experimental design. Therefore, random assignment is most related to internal validity. After all, we randomly assign in order to help assure that our treatment groups are similar to each other prior to the treatment. There are also three common ways to randomize participants. Simple randomization maintains complete randomness of the assignment of a subject to a particular group. The most common and easiest method of simple randomization is flipping a coin. For example, with two treatment groups (control versus treatment), the side of the coin (heads - control, tails - treatment) determines the assignment of each subject. Some researchers like to use spreadsheet software such as Microsoft Excel to use his method as well. The second method is block randomization. The block randomization method is designed to randomize subjects into groups that result in equal sample sizes. This method is used to ensure a balance in sample size across groups over time. Blocks are fairly small and balanced with predetermined group assignments, which keeps the numbers of subjects in each group similar at all times. The third method is adaptive randomization. In adaptive randomization, a new participant is sequentially assigned to a particular treatment group by taking into account the specific covariates and previous assignments of participants. Adaptive randomization uses the method of minimization by assessing the imbalance of sample size among several covariates.
Researchers can draw conclusions without randomization by using a variety of research methods. Prospective data or retrospective data come to mind. Prospective data is data that’s collected as behavior or a reaction. Retrospective data refers to data that was collected back in time, generally from historical records. Both of these methods of data collection can draw conclusions even though it’s not randomized. This would allow researchers to assess causality without randomization.
Randomization plays a major role in eliminating researcher bias, creating a possibility to develop statistics and is the preferred method for researchers to insure validity. Although you don’t always have to perform randomized research to collect valid data, it’s the preferred method for most types of research.
References
Gigerenzer, G., Swijtink, Z., Porter, T., Daston, L., Beatty, J., Kruger, L. (1989). The empire of chance: How probability changed science and everyday life. New York, NY: Cambridge University Press
Kirk, R. E. (2000). Randomized experiments. Encyclopedia of psychology (vol, 6, pp. 502-505). New York, NY: Oxford University Press & American Psychological Association.
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