Understanding Quasi-Experimental Quantitative Research Design

What is Quasi-Experimental Research?

Quasi-experiments are research designs that aim to test a hypothesis by manipulating a variable but not through random assignment. Unlike experimental design where the researcher randomly assigns subjects to control and treatment groups, here non-random method is used to assign subjects to groups.This method of research is similar to that of a true experiment, but it is not classified as a true experimental research. Rather than combining random assignment with control over the independent variable, quasi-experiments use some other criterion to determine who participates in the experiment. 

The two main types of quasi-experiments are propensity score matching and case-control study. Propensity score matching is a statistical method used in a quasi-experiment to match groups on the basis of certain factors. For example, say we want to know whether receiving an academic award affects a student’s chances of graduating in four years. We might gather data on all students, but only four will receive an award. In this case, each student is a lottery winner and will be in one group. We don’t know which lottery winners receive the award, only that four of them do. Propensity score matching uses other data on various factors about the subjects to estimate the odds of winning the lottery, based on the same factors. We then compare the lottery winners with the non-winners to estimate the odds of winning based on whether they were in the treated or untreated group. After matching the lottery winners with the non-winners to get their predicted lottery-winning chances, we compare the two groups. The odds of winning the lottery in both groups don’t change, but, if we know the effect of the award, we can estimate the effect of the award by subtracting the odds of winning for non-winners from the odds of winning for lottery winners, and multiplying the result by the effect of the award.

Example of Quasi-Experimental Research Design

For example, researchers may want to find out if a monthly allowance for children does affect their academic performance, or whether it has no effect at all. Propensity score matching can be used to match the treatment group with the control group by matching the children who receive the monthly allowance with those who do not. The treatment group is then compared to the control group. If the treatment group outperforms the control group, the researchers can infer that the allowance has an effect. The key to this type of research is to find a way to do the matching so that the groups are as similar as possible.

Research Questions and Limitations of Quasi-experimental Research

In quasi-experimental research, researchers try to control the factors that affect their research results. To do this, they control certain factors related to the research, such as the type of research design used, how the research was conducted, or the timing of the data collection. Researchers may control factors related to their participants too, such as the social or academic backgrounds of the participants. By controlling these factors, the researchers hope to reduce the effect of other factors that are harder to control, such as the participants’ implicit attitudes towards the research topic. Researchers may also try to minimize the effect of their own biases and preconceptions about their research topic.

Experimental Research Design

In experimental research, researchers try to manipulate or control the factors that affect their results. In an experiment, the researchers try to show that one factor causes changes in some other factor. This communication between factors is called an association. The association may be direct, such as a cause and effect, or indirect, such as an association between two factors. To see if the association is real, the researchers must conduct an experiment. There are many different types of experiments. The most common experimental designs are randomized control trials, quasi-experiments, and experiments with control groups and experiments with paired comparisons.

Conclusion

When it comes to research design, we have both controlled experiments and controlled observations. Controlled experiments are the most reliable way to test or validate a hypothesis or theory because each participant is assigned at random to one of the two groups. A result observed in a controlled experiment has a greater chance of being accurate than any other type of research. Controlled observations are the least reliable because they don’t have random assignment of participants to groups so any results are just observations and may be inaccurate.