Definition
Causal comparative research: non-intervention research design aimed at uncovering relationships by comparing groups of people who already differ on a variable of interest. It uses designs that search for causes or effects of a preexisting factor of interest. The preexisting factor differentiates groups and permits a meaningful comparison (e.g., examining achievement differences between children in one-parent and two-parent families). (Suter, 2012, pg. 4)

Causal comparative research design, also known as ex post facto research, is a non-experimental method used to identify potential cause-and-effect relationships between variables. Researchers analyze existing differences among groups to determine how one variable may influence another without manipulating the variables themselves. (Wikipedia)

Notes
Causal comparative research is well suited for uncovering relationships and forming theories that might be tested in followup studies using experimental or quasi-experimental research to better illuminate causal connections. (pg. 8)

Educational researchers must frequently study phenomena as they naturally occur, without intervention of any sort. This is because it may not be practical, ethical, or feasible to arrange for the occurrence of a factor believed to cause some effect. For example, the influence of divorce on the educational achievement and motivation of young students can only be studied without intervention. ( Can you imagine randomly assigning married couples to a divorce group or high school students to a dropout group?) (pg. 5)

We also saw in Chapter 3 that researchers who study preexisting group differences ( attributes ) refer to their designs in general as causal comparative. Causal comparative research is so named because the researcher is comparing different groups in an effort to explain presumed causes ( or effects ) of such differences.

There are hundreds more attribute variables that are considered important, but not all are readily amenable to experimental manipulations with random assignment.

causal comparative studies are not well suited to disentangling cause and effect relationships. They are comparative (in procedure) but not causal (in logic), despite the design's label.

Causal comparative research compares groups that differ on a preexisting attribute (not independent) variable. As such, this type of non-intervention research is not well suited to establish cause and effect, despite the word causal in its label.

Other causal comparative designs may focus on a presumed effect of some cause.

Whether the researcher is forming groups out of an interest in a cause or an effect, the basic design is the same. Groups are formed on some basis (a presumed cause or a presumed effect), then compared on another variable to shed light on the basis of the relationship (pg. 7)

To repeat this for emphasis: Despite the general name for these types of designs—causal comparative—such designs are far weaker than experimental designs for establishing cause and effect.

Several design considerations greatly enhance the usefulness of causal comparative research in education, including how groups are formed (selected), how control procedures (e.g., matching) are used, how persuasively alternative explanations are ruled out (e.g., by strong inference), and how well spurious relationships are uncovered and controlled.

Design controls

For example, a matched control group design would involve selecting two groups that are dissimilar on the hypothesized cause, say, bottle-fed and breastfed babies, but are the same on a matching variable believed to be a rival explanation, say, the age and socioeconomic status of the mother. (pg. 8)

An extreme groups design would involve the selection of groups that represent maximum differences on the hypothesized cause (or effect)—for example, those who watch 60 or more hours of television per week and those who watch very little or no television.

Example (AI generated)
Sure! Based on the chapter's definition of causal comparative research design, an example of a case study could be:

Example Case Study: Impact of Parenting Styles on Academic Achievement

Objective: To investigate how different parenting styles (authoritative, authoritarian, permissive) affect the academic performance of high school students.

Method:

1. Participants: Select groups of students from various schools who have been classified based on their parenting style.
2. Data Collection: Gather academic records (like GPA) and conduct interviews or surveys with students about their perceptions of their parents' styles.
3. Analysis: Compare the academic performance of students from each parenting style group to identify any significant differences.

This case study would highlight the relationships between preexisting variables (parenting styles) and outcomes (academic achievement) without manipulating any factors, fitting the causal comparative research design.

Google Gemini (2025)

Key Characteristics

Non-Experimental Nature

• Researchers do not manipulate independent variables.
• Observations are made on naturally occurring differences.

Group Comparison

• Involves comparing two or more groups based on pre-existing differences.
• Groups are selected based on characteristics relevant to the study, such as socioeconomic status or educational background.

Types of Causal Comparative Research

Retrospective Comparative Research

• Investigates past events to identify relationships between variables.
• Useful when it is impractical or unethical to conduct experiments.

Prospective Comparative Research

• Follows participants over time to observe outcomes based on initial conditions.
• Less common than retrospective studies.

Applications

Causal comparative research is widely used in fields like education, healthcare, and social sciences. It helps researchers understand how various factors impact outcomes, such as the effects of educational interventions or health behaviors.

Advantages and Disadvantages

Advantages

• Efficient in terms of time and resources.
• Can identify causes of existing differences among groups.

Disadvantages

• Establishing direct causality can be challenging due to lack of control over variables.
• Results may be influenced by confounding factors not accounted for in the study.