Causal Comparative Researh

A causal-comparative design is a research design that seeks to find relationships between independent and dependent variables after an action or event has already occurred. The researcher's goal is to determine whether the independent variable affected the outcome, or dependent variable, by comparing two or more groups of individuals. There are similarities and differences between causal-comparative research, also referred to as ex post facto research, and both correlational and experimental research. This entry discusses these differences, as well as the benefits, process, limitations, and criticism of this type of research design. To demonstrate how to use causal-comparative research, examples in education are presented.

Similarities to correlational research:

• Both types of research are examples of associational research:
• Researchers seek to explore relationships among variables
• Both attempt to explain phenomena of interest
• Both seek to identify variables that are worthy of later exploration
• Often provide guidance for later experimental studies
• Neither allow the researcher to manipulate the variables
• Both attempt to explore causation

Differences between causal-comparative and correlational research:

-Typically compare 2 or more groups of subjects vs requires a score on each variable for each subject

- Involves at least 1 categorical variable vs investigate 2 or more quantitative variables

- Analyses data by comparing averages or uses crossbreak tables vs analyzes data by using scatterplots and/or correlation coefficients.

Below is the notes I made for the upcoming quiz. Hopefully it will help me pass the quiz and able to answer questions related to causal-comparative research methodology clearly.