Essay on the Static Group Comparison Design and the Multiple Time Series Design

Designing a study for an experiment enables one to describe and explain why there is a variation in the information or results obtained. For the variation to be well explained there is a need to have a set of theorized conditions, which reflect the observed variation. An experimental design is associated with experiments whose design brings forth the conditions that determine the extent of the variation. Typically, an experiment predicts the result by changing the preconditions represented by the predictor or the independent variable. This change is theorized to bring about a change in the outcome or dependent variable. An experimental design can be used in scientific as well as social studies. This paper aims at discussing how one can design a study to evaluate the effectiveness of a treatment for batterers.

If the study were a pre-experimental design, I would use the static group comparison to evaluate whether the treatment of the batterers was effective. In a static group comparison, the outcome of the experiment is measured after the intervention has been implemented. In this case, the effectiveness of the treatment is measured after the treatment has already been administered. However, to come up with the correct measurements, there is a need to have a control group. The static group comparison provides this option. Hence, in the case of the batterers, I would choose one group to undergo treatment and a second one to remain without treatment. Once the treatment has been administered, I would record the findings from each group. The first group would likely produce different results from the second group. If the results were positive, such that they are better than those of the second group are, then the treatment would have been effective. However, if the first group does not produce positive results, such that they remained similar to those of the second group, then the treatment would have been ineffective. The static group comparison design is more suitable in this study since it includes a control group. However, the selection of the participants may result in two groups of batterers, which have different significant variables.

If the study were an experimental design, I would choose the pretest-posttest control group. This design measures change in the outcome before and after the intervention. The design also includes two groups of participants selected randomly. In the case of the batterers, I would also create two groups from a pool of participants. After this, I would record the necessary measurements of the members in each group before administering the treatment. Then I would provide one group with the treatment and leave the second one without. Once the treatment is over, I would record the measurements from each group. The measurements from the first group would most likely be different. If the results were different such that they exhibit a positive change, then the treatment would have been effective. However, if the results were negative such that they are similar to that of the second group, then the treatment would have been ineffective. Aside from this, the pretest-posttest control group design is appropriate in this stage since it provides a causal relationship between the intervention and the outcome. Hence, if the first group produced positive results, then there was a causal relationship between the treatment and the outcome. However, if the first group produced negative results, then there was no causal relationship between the treatment and the outcome.

If the study were a quasi-experimental study, i would use the multiple time series design. This design is used to measure a trend over a given period. The design also includes measurement of a trend before and after an intervention. There are two groups selected from a pool of participants. One group receives the intervention while the second one does not. Also, the data collected is based on various time points. In the case of the batterers, I would select a number of participants randomly and put them into two groups. I would then record measurements at various time points over a given period e.g. three months. After the three months, I would provide the first group with the treatment and leave the second group without. Three months after treatment, I would record measurements on the same time points I had recorded before. If the results from the first group of batterers were positive, then the treatment would have been effective. However, if the results were negative such that they are not different from those of the second group, then the treatment would not have been effective. The multiple time series design is suitable for this study. However, the process of selecting participants could also result in two groups of batterers that have different relevant variables.

The static group comparison design and the multiple time series design have the same weakness as seen above. However, in my opinion, the two designs are the most suitable for this study. There is a need to further the research on pre-experimental and quasi-experimental designs to establish a reliable design such as the pretest-posttest control group design.