Difference between causal comparative and experimental research design

Causal-comparative research design, also known as experimental research design are two distinct approaches used in social science research to investigate cause-and-effect relationships.

While they some similarities, there are key differences between these two designs-

Causal-Comparative Research Design: Causal-comparative research design aims to explore and understand causal relationships by comparing existing groups that have already experienced different treatments or conditions. It is often used when it is not feasible or ethical to manipulate variables or randomly assign participants to groups. In causal-comparative research:

Independent Variable: The independent variable (treatment or condition) is not manipulated by the researcher but naturally occurs or has already occurred.

Group Comparison: Researchers identify groups that have been exposed to different conditions or treatments and compare them on the dependent variable of interest. These groups are often pre-existing or naturally occurring, such as different schools, age groups, or genders.

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Retrospective Design: Causal-comparative research is typically retrospective, meaning that the researcher collects data after the treatment or condition has already occurred.

Limited Control: Researchers have limited control over extraneous variables and potential confounding factors that may influence the relationship between the independent and dependent variables.

Difference between causal comparative and experimental research design-As a result, establishing causality becomes more challenging compared to experimental research.

Experimental Research Design: Experimental research design, on the other hand, is a controlled research design that allows researchers to manipulate independent variables and randomly assign participants to different conditions or groups.

Difference between causal comparative and experimental research design-Experimental research is characterized by the following elements:

Manipulated Independent Variable: Researchers actively manipulate and control the independent variable(s) by assigning participants to different experimental conditions. This allows for a clear cause-and-effect relationship to be established.

Random Assignment: Participants are randomly assigned to different conditions or groups to ensure that any differences observed in the dependent variable(s) are due to the manipulation of the independent variable(s) and not pre-existing differences between participants.

Prospective Design: Experimental research is typically prospective, meaning that data is collected after the manipulation of the independent variable(s) but before any potential effects occur.

High Control: Experimental research provides researchers with a high degree of control over extraneous variables, allowing them to isolate the effects of the independent variable(s) and establish causal relationships more confidently.