The Nature of Causal-Comparative Research
- Causal-comparative research, like correlational research, seeks to identify associations among variables.
- Causal-comparative research attempts to determine the cause or consequences of differences that already exist between or among groups of individuals.
- The basic causal-comparative approach is to begin with a noted difference between two groups and then to look for possible causes for, or consequences of, this difference.
- There are three types of causal-comparative research (exploration of effects, exploration of causes, exploration of consequences), which differ in their purposes and structure.
- When an experiment would take a considerable length of time and be quite costly to conduct, a causal-comparative study is sometimes used as an alternative.
- As in correlational studies, relationships can be identified in causal-comparative study, but causation cannot be fully established.
Causal-Comparative versus Correlational Research
- The basic similarity between causal-comparative and correlational studies is that both seek to explore relationships among variables. When relationships are identified through causal-comparative research (or in correlational research), they often are studied at a later time by means of experimental research.
Causal-Comparative versus Experimental Research
- In experimental research, the group membership variable is manipulated; in causal-comparative research the group differences already exist.
Steps in Causal-Comparative Research
- The first step in formulating a problem in causal-comparative research is usually to identify and define the particular phenomena of interest, and then to consider possible causes for, or consequences of, these phenomena.
- The important thing in selecting a sample for a causal-comparative study is to define carefully the characteristic to be studied and then to select groups that differ in this characteristic.
- There are no limits to the kinds of instruments that can be used in a causal-comparative study.
- The basic causal-comparative design involves selecting two groups that differ on a particular variable of interest and then comparing them on another variable or variables.
Threats to Internal Validity in Causal-Comparative Research
- Two weaknesses in causal-comparative research are lack of randomization and inability to manipulate an independent variable.
- A major threat to the internal validity of a causal-comparative study is the possibility of a subject selection bias. The chief procedures that a researcher can use to reduce this threat include matching subjects on a related variable or creating homogeneous subgroups, and the technique of statistical matching.
- Other threats to internal validity in causal-comparative studies include location, instrumentation, and loss of subjects. In addition, type 3 studies are subject to implementation, history, maturation, attitude of subjects, regression, and testing threats.
Data Analysis in Causal-Comparative Studies
- The first step in a data analysis of a causal-comparative study is to construct frequency polygons.
- Means and standard deviations are usually calculated if the variables involved are quantitative.
- The most commonly used test in causal-comparative studies is a t-test for differences between means.
- Analysis of covariance is particularly useful in causal-comparative studies.
- The results of causal-comparative studies should always be interpreted with caution, because they do not prove cause and effect.
Associations Between Categorical Variables
- Both crossbreak tables and contingency coefficients can be used to investigate possible associations between categorical variables, although predictions from crossbreak tables are not precise. Fortunately, there are relatively few questions of interest in education that involve two categorical variables.