No experimental approaches Causal-Comparative and Correlational Research
Rose is a counselor at an urban high school. She frequently talks with students who are working while they attend high school. Although Rose knows that students value their spending money, she is concerned that working might interfere with their studies. She wonders if there is a difference in grades between students who work and those who do not.
She decides to collect some data to examine her hypothesis that students who work will have lower grade point averages than students who do not work. When she meets with students, she asks them if they are employed and how many hours a week they work. After a couple of months, she soon has records on the employment status of over 100 students.
Steps in Causal-Comparative Research
Causal-comparative research often looks deceptively simple. One identifies two groups that had different experiences and then measures how this affected them. However, high-quality causal-comparative research requires careful thinking at each stage. The steps involved in doing causal-comparative research are summarized below.
Reviewing Literature to Identify Important Variables
The researcher reviews literature to identify what research has revealed about the impact of the past experience on later behavior. Potential extraneous variables might also be identified through the review of literature. For example, if one was examining the leadership positions of women who attended same-sex versus coed colleges, one might find that students at single-sex colleges tend to come from families with higher levels of income and education.
Also, the researcher might find useful information about the methods used to select samples in past studies or measure possible dependent variables. If one wanted to compare children with a history of abuse and those with no history of abuse, studies might reveal how these researchers were able to identify possible participants.
Based on a review of the literature, one would identify an independent variable (prior experience or group difference that cannot or should not be manipulated) and a dependent variable that might be affected by this independent variable.
Selecting Participants Using Procedures to Control Extraneous Variables
Unlike experimental research, the participants in causal-comparative research already belong to groups based on their past experiences, and so the researcher selects participants from these preexisting groups. An important consideration in designing causal-comparative studies is whether the two groups are similar except for the independent variable on which they are being compared.
If two groups are formed because they differ on the independent variable, but they also happen to differ on other extraneous variables, the researchers will not know whether group differences on the dependent variable are caused by the independent or extraneous variables.
Selecting Reliable and Valid Measuring Instruments
Selecting appropriate instruments is an important issue in all types of quantitative research. A researcher interested in the question of same-sex versus coed colleges and leadership positions would certainly need to find or develop a measure that accurately measured the dependent variable or types of leadership positions participants had held.
Although researchers use descriptive statistics to analyze data, studies that want to make inferences about the population from which the sample was drawn require a higher level of analysis to be conducted. Tests used to make inferences about a population based on a sample are referred to as inferential statistics.
Correlational studies, causal-comparative studies, and experimental studies employ the use of inferential statistics to draw conclusions. In experimental research, the researcher wants to know if the experimental treatment caused a difference between the two groups and hopes to make generalizations of the findings back to a wider population by using randomization procedures.