There are three types of quantitative methods of study: correlational, experimental, and quasi-experimental. To some degree each of these designs allows the researcher to identify relationships between different factors and to then specify the causes of these relationships. The initial responsibility of the researcher is to find the general design that tests the hypothesis with the maximum amount of clarity.
The correlational design is used to determine whether relationships exist between two or more variables. Ultimately the investigator wants to determine whether a change in one variable coincides with a change in a second variable. In a correlation design no variable manipulation occurs. For example, a child's behaviors are measured as they naturally occur, and a numerical index reflecting the relationship between the measures' outcomes is then computed. Usually, a correlation coefficient is used to calculate the strength and type (positive or negative) of relationship that exists. While the correlational design is extremely useful, it cannot be used to determine cause-effect relationships between variables. The primary reason for this is that variables other than the ones under study cannot be controlled, measured, or otherwise considered in the correlational design; such variables could influence the relationship between the variables under study. This kind of control is afforded only in designs in which variables can be manipulated and participants can be randomly assigned to groups.
An experimental design does allow cause-effect conclusions since variables can be manipulated and participants can be randomly assigned. With respect to manipulation of variables, the researcher must assign independent and dependent variables to the experiment. The independent variables are the various treatments that the participants receive (and that are manipulated by the researcher), while the dependent variable represents the responses of the participants. For example, an independent variable might represent the amount of direct reading instruction students receive, and the dependent variable might be reading achievement scores. In essence, the researcher wants the dependent variable to reflect the effect of being treated with the independent variable. Experimenter control of the independent variable (e.g., amount, duration, and type of treatment) partially affords the necessary confidence to reach cause-effect conclusions. In other words, differences in the dependent variable may then be attributed to the various treat ments the participants received (in the example, differences in reading achievement scores may be attributed to the various amounts of direct reading instruction).
In order to say that the treatment has caused some effect (on the dependent variable), it is important that all the traits of the participants be about the same, especially those that could confound the study. One way to accomplish such group equality is to randomly assign participants to groups. In essence, when "chance" is the force behind who gets the various treatments, it is assumed that the groups contain participants who were more or less alike prior to receiving treatments.
The ability to gain the necessary control that allows for cause-effect conclusion is also an important shortcoming of the experimental design. Conducting research in a controlled setting may alter the natural behavior patterns of participants and therefore decrease the "ecological validity'' of the results. The researcher must also stay within ethical bounds, meaning that treatments that have adverse physical or psychological effects on participants cannot be used. Finally, the requirement of random assignment may not be possible for ethical or practical reasons.
To counter the latter drawback to the experimental design, a researcher might turn to the quasi-experimental design. The quasi-experimental method permits the researcher to compare groups that have been manipulated but not randomly assigned. For example, in the above example of a study of the effect of direct reading instruction on reading achievement, suppose that homerooms have already been assigned in the school where the researcher intends to conduct the study. It may still be possible to treat different classes, but the researcher must take into account that the participants were not randomly assigned to the classes. In such a case, a quasi-experimental design could be used, but the researcher must temper any cause-effect conclusions because of the possibility that uncontrolled variables "caused" the results.
Finally, it may not be possible to manipulate variables or randomly assign participants to groups. In this case, a causal comparative design might be used. In the causal comparative method, already existing groups are studied (after the "independent variable'' has already occurred) and group differences are studied on some dependent variable of interest. For example, a researcher might choose to study the intellectual development of children in orphanages compared to that of children raised in a home setting with their biological parents. The causal comparative design is often used to study treatments that would be unethical to impose on participants. Obviously, the causal-comparative design offers little of the control necessary to make cause-effect conclusions.
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