Quantitative causal-comparative research: definition, types, methodology, methods, characteristics, examples and advantages

How do we define the term quantitative causal-comparative research? Is it the same as quantitative descriptive research or quantitative correlational research? Look at this…

1.1 Definition:

Quantitative Causal-Comparative Research is a non-experimental type of research which involves investigating the cause of differences in behavior for two groups which are similar or the same. The concern of the researcher is to find out the reason why a certain condition which has been exposed to a certain group of people have different results when subjected to another similar group in the future. For example, the investigator may wish to interrogate why youth in school who went through corporal punishment are highly disciplined in all what they do in the society as compared to youth in the current times when they are subjected to the same corporal punishment in school.

You see, this type of research has an element of comparison and again there is no manipulation of the variable under study. The researcher is looking at youth in school in both cases and the punishment is of corporal nature. Causal-comparative research designs are also referred to as ex- post facto research design. That is, research where by the researcher looks at the “after-the-fact” situation or scenario. The reason for this is that the study first observes a difference that exists within a group of people who are from a similar group.

In this kind of research, the investigator selects two groups for comparison to establish the cause for the difference already noticed. Now, you should not confuse the quantitative causal-comparative research with experimental research where cause-effect link is pronounced. This is because in the case of causal-comparative research, the cause may not be true cause and again none of the variables being studied is manipulated. In the case of experimental research for your information as we shall see, there is true cause because the independent variables are manipulated.

1.2 Assumptions of quantitative causal-comparative research

i). Independent variable is always assumed to have already occurred.

ii). The main concern of the researcher is the changes occurring on the dependent variable.

iii). There is a difference between two similar groups.

iv). The groups are similar by all standards.

v). The independent variable is the grouping variable for it is the one associated with causing the two groups look different.

vi). Independent variable naturally pre-exists. i.e., the condition had already occurred (the fact).

vii). Independent variable cannot be manipulated.

NB: In our current discussion, we are adding the word “quantitative” so as to simply highlight that the variables are gauged using numerical terms.

Types of quantitative causal-comparative research

There are two main types of quantitative causal-comparative research as explained below;

1.Retrospective Causal Comparative Research

This is research where by the researcher forms the research problem or forms the research question after the effect caused by the independent variable has occurred. The researcher attempts to find out whether or not a variable influences another variable.

2.Prospective Causal Comparative Research

This is research where by the researcher proposes or postulates the research problem or the research question before the effect caused by the independent variable has occurred. The researcher attempts to find out whether or not a variable CAN influence another variable. It is a rare practice for that is not what is expected.

Example of Quantitative Causal-Comparative Research

The following is an illustration of how causal comparative research works. First, let us remind ourselves what kind of research is this. This is research which the researcher endeavors to trace a cause-effect relationship between the independent and dependent variable in a situation whereby the independent variable (commonly referred to as self-selecting independent variable) cannot be manipulated due to the fact that it has already occurred.

So, suppose the researcher wants to test the high chances of conducting HIV Aids amongst the youth in a certain city. The researcher will identify two groups

Group one-youth which have engaged themselves in sex workers activity and

Group two-those who are not engaged in sex workers activity, maybe they are in school.

The researcher tests the HIV Aids status of both groups. If group one which have entangled itself in sex workers activities in the city have more members having the infection as compared to those in school, then it can be concluded that sex workers activity is the cause of high rate of HIV Aids infection in that city.

Quantitative causal-comparative research methodology

Does quantitative causal-comparative research methods for formulating a research problem the same as quantitative causal-comparative research method for data analysis? The answer is NO. Look at the definitional differences as per our explanation below.

3.1 Definition

Quantitative Causal-Comparative research Methodology is the reasonable progression or step by step design on how to solve a research problem through gathering of the relevant information. Quantitative Causal-Comparative research methodology entails selection of logical procedure on the topic to be studied. That is the research problem, how specific objectives will be identified/or formulated. Identification of knowledge gaps to be filled, research hypotheses to construct, the methods utilized to identify population and sample size, nature of data to be collected and how it will be analyzed, data presentation and interpretations thereof and the reporting of the research findings.

The aforementioned description on quantitative causal-comparative research methodology is in tandem with Kothari (1984) proposal who was of the idea that research methodology is the foundation behind the methods we use in the context of our research study. This provides a logic as to why one is using a particular method or technique at a particular stage in the research process and not others so that research output is accomplished as expected.

3.2 Questions quantitative causal-comparative research Methodology tries to Answer

The quantitative causal-comparative research question focuses on influence of the predictor variable on the dependent variable where by the predictor variable is not manipulated. In other words, it is invariant. For example, “Does height level determine the athlete’s sports performance?” this is an example of a descriptive causal-effect research in which the researcher is primarily interested in causal connection.

This is an example of a quantitative causal-comparative research in which the researcher is primarily concerned with difference between two groups, seeking to establish a cause-effect association. So, this study tries to answer “What” kind of questions.

The following matrix depicts the link between quantitative causal-comparative research and the type of research methodology adopted and then a clarification of the rational approach linked with this type and then in the last column, the research method(s) used in formulating the research problem. Remember these methods are specifically for quantitative causal-comparative research which is a sub-set of Quantitative research.

3.3 Quantitative Causal-comparative research Methodology-Diagrammatic Approach

The following diagram represents a summary of logical roadmap to be adhered to in quantitative causal-comparative research methodology where Quantitative or Numerical methods are used to measure/gauge the study variables.

3.4 Logical Steps; Basic Research Methodology

The following logical steps describe the Quantitative causal-comparative research methodology. From step one to six, it represents a logical way of how systematically the subject matter need to be dealt with. Remember that in this approach, the researcher is only curious of establishing why similar groups differ with one another.

Step 1: Identify the Topic of the study

In this case, which entails causal comparative viewpoint, the researcher formulates the research problem in mind that there are causes of the difference seen the groups of focus and therefore he/she approaches the matter in a logical manner for the aim of the study is to investigate the cause of differences between two or similar groups. So, the choices of groups made must be making sense or be plausible.

Once the researcher identifies probable causes (independent variables), they are used to establish the research question, hypothesis or research problem. Therefore, the research question or hypothesis will be framed in a way to portray the difference being investigated. For example, a research question can be framed as follows;

“How does Covid-19 Vaccination amongst the old-65 years versus Un-vaccinated old-65 years affect immunity to Corona attach in Dubai?”

OR

“Does age have an effect on heart health complications-breathing problem?”

Step 2: Literature Review

The researcher has to undertake literature review which is a process of re-visiting the past literature which is related to similar studies addressing the same variables. This approach helps the researcher to identify possible causes or consequences of a particular difference.  The review aid in identification of the contextual, methodological and conceptual or theoretical research gaps which is the impetus for the current Quantitative Causal-comparative research.

Step 3: Selection of Research Participants

Unlike the other non-experimental research, the researcher needs to be extra careful when selecting the groups to participate in this type of research. This is because the investigator needs to take note of the following aspects;

-Need for proper definition of the independent variable for they are used as the grouping variables.

-Need to select groups with significant differences which is measurable.

-Need to select homogenous groups.

-Need to control extraneous variables that can interfere with the set assumption of quantitative causal-comparative research.

Step 4: Data Collection

The process of data collection in this stage is flexible for there is no one way which is strictly followed to collect data. But so long as sufficient and relevant data is collected, any instrument can be used to achieve this goal. There is no law to that.

Step 5: Data Analysis

Data analysis for quantitative causal-comparative research based on both the descriptive and inferential analysis models. This is then followed by the statistical comparison of two or more groups on some quantitative benchmark. 

Step 6: Research Findings and conclusions

In this step, the researcher has performed various data analysis and the outcome is ready for reporting and provision of conclusions. In this stage, the researcher has established whether the identified independent variables are the causes of the differences between the two groups. It is then at this point where he/she concludes of the presence of causing variables although not very easy to do so.

Quantitative causal-comparative research methods

4.1 Definition

Research methods are the procedures that are applied in all the phases of research developments. They are apparatuses used to guarantee the end consequences of research task are accomplished. These techniques vary from one stage of research process to another. These methods are further classified in to two categories, namely;

a) Pre-Data analysis methods

b) Data Analysis related methods

As per Table 1.1 in this article, quantitative causal-comparative research methods indicated in that table (refer), namely survey, systematic observation and secondary research methods for the purposes of formulating the research problem and are some of the methods which fall under pre-data analysis category.  However, in this discussion of quantitative causal-comparative research methods, you should appreciate that there is no distinct way of collecting data as long as the data collected is authentic for data analysis.

Characteristics of quantitative causal-comparative research

1. Justifies the reasons as to why similar groups are different
2. Ex post facto-this type of research is such that the cause has already occurred or happened before the researcher arrives.
3. Causal-comparative research describes conditions that already exist.
4. Cause-effect relationships-the research portrays that there are causes of the differences.
5. Comparison is the bottom line of this research.
6. Characterized by two (or more) groups and one independent variable.
7. Involves comparison of two or more groups on a single endogenous variable.
8. Reversed study for the researcher looks for the effect, then look for the cause later
9. The two groups apparently look alike until the researcher is guided otherwise.

Advantages of quantitative causal-comparative research

1). Cost effective-since this research tests possibility of cause-effect relationship, it helps the researcher to minimize his/her resource allocation on experimental research.

2). Causal-comparative research helps in finding out where there is a possibility of a cause-effect relationship before experimental research is performed which may involve more resource allocation.

3). Used in circumstances where the researcher is avoiding use of experimental research which may force the researcher to break ethical, safety or legal rules related to human rights.

4). Help in assessing impacts of changes on existing customs, procedures etc.

5). No researcher biasness-since the variables are not interrupted/not manipulated.

Disadvantages of quantitative causal-comparative research

1. Time consuming-causal-comparative research takes a lot of time for it involves comparison of two or more groups for a longer period so as to be in a position to make conclusions.
2. Extraneous variables may portray non-sense relationship. That is, an apparent cause-effect relationship may not be what it seems.
3. The researcher has no control of the variables. For example, the so called self-selected independent variable usually occurs before the researcher’s action. For example, when the respondent is already a smoker. Has already chosen the character of smoking.
4. Causes and effects may be reversed. Sometimes the suspected cause-effect relationship may be the opposite. Such that a group that is under control may portray a significant difference as compared to the experimental group. For example, testing two groups for cancer due to smoking. Those who don’t smoke may be more affected of cancer than the smokers themselves. These results are contrary to the expectations of the investigators.