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What Is Best Research Approach For Gathering Causal Information?

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Causal research is a type of study that focuses on determining the causal relationship between variables. Researchers assess the cause and effect relationship between the variables. It helps in understanding the cause of a particular phenomenon. We can use causal research to determine what changes occur in an independent variable due to a change in the dependent variable. But, to analyze the causal relationships, a researcher must devise a strategy for gathering causal information. This article will guide you on the best approaches to gathering causal information.

What is a causal research approach?

Causal research is a kind of scientific study that aims to find a cause-and-effect link between two or more variables. Causal research is a consequence of correlational and exploratory research. Causal research is often the last step in the research process. It is because correlational and exploratory research builds the foundation for causal research. Correlational research uncovers and analyses correlations between two variables. But, it does not establish that one variable causes the other variable to act in a certain manner or conversely.

On the other hand, causal research can analyze the impact of one variable over another. In the causal research approach, it is easy to pinpoint causal connections. The approach involves ensuring that the impact of other factors on a variable is negligible. It helps in ascertaining the impact of one variable over another. The approach presupposes that the other variables are constant to ensure precision. It can assist in determining the precise impact that one variable has over another. The research approach for causal research is very structured and strict. Therefore, it is necessary to hire dissertation proposal writing services. Causal researches design has the following features:

Temporal Sequence

There must be a chronological order to the events. The “cause” must occur before the “effect”. There could be a strong relationship between two factors at a single point in time. But we cannot ascertain which one is the dependent variable and which is the independent variable. For instance, there is a strong correlation between people with low incomes and their drinking habits. But, it is presumptuous to conclude that low incomes cause people to drink. There can be another possibility that since they have a drinking habit, their incomes are low because they don’t perform better in their jobs.

Concomitant variation

Concomitant variation refers to the change that occurs equally in “effect” with the equal change in the “cause”. It implies that the variation between the variables must be systematic. For example, if a company fired most of its skilled employees and its revenue fell, we will infer that the decline in revenues is due to the expulsion of skilled employees.

Nonspurious Association

A cause and effect relationship’s correlations must be accurate and not due to a third element that could affect both. For example, sometimes intervening variables better explain the cause behind an effect. Non-spurious association refers to eliminating the impact of any third factor while determining the causal relationship between two variables.

Is causal research quantitative or qualitative?

Causal research is generally quantitative. However, many social sciences academics argue that qualitative methods have the potential to determine causality. The major aim of causal research is to establish the relationship between two or more variables. In natural science, it is evident that when researchers try to understand the impact of X on Y, they utilize quantitative methods. But when it comes to social sciences and understanding the social phenomenon, causality cannot be quantified. It is because there are so many intervening variables involved. Society is not a closed space that can be quantified by assigning numbers. Human life is a complex phenomenon where causality cannot be ascertained with mathematical precision.

For example, a political scientist wants to ascertain the impact of an independent variable on a dependent variable. The possibilities of establishing an independent variable are numerous. It is because an independent variable could be a dependent variable, or the relationship between two variables might be affected by another factor. So, based on this logic, we can infer that we cannot isolate causal research to only quantitative methods when it comes to social sciences. In social sciences, causal research can be both quantitative and qualitative.

Which data collection method is used in causal research?

Experimentation is the most popular method of gathering causal information. Experimentation is highly preferred in gathering causal information because it fulfills the following criteria:

  • Temporal Sequence
  • Concomitant variation
  • Nonspurious Association

Researchers use the following methodology for gathering causal information:

  • Researchers select two comparison groups to establish causality. One group is the experimental group, and another is the control group
  • To ascertain the temporal sequence, researchers manipulate the independent variable.
  • They evaluate the impact of changes in an independent variable on a dependent variable. After that, they make changes in the dependent variable to see its impact on the independent variable
  • Researchers randomly assign two or more comparative groups to fulfill the criteria of nonspurious association

In a causal experiment, researchers can assess the link between independent and dependent variables by the following criteria:

  • If the two or more groups show variations if changes are made in the independent variable
  • In the case of the experimental group, researchers make variations in the independent variable
  • In the case of the control group, researchers do not make any changes in the independent variable


Causal research is an important research design that comes after correlational and explanatory research. Researchers employ experimentation for gathering causal information and to ascertain the impact of one variable over another. As mentioned above, the three causal research approaches are necessary to establish causality.   Researchers develop experiments to analyze causality because so many factors can tamper with the objectivity of research. They evaluate the data and examine the reasons behind the linkage between two variables. Researchers also tamper with the independent variable to see its impact on the dependent variable on more than one group of people.

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