A proposal to evaluate handgun restriction laws for intimate partner homicide across gender and race Research goals

1196 Words3 Pages

Cause, effect, and causal relationship In order to describe research designs, I first need to define what is cause, effect, and causal relationship (Shadish, Cook, & Campbell, 2002). A cause is a factor that occurs a certain condition. An effect is understood through a counterfactual reasoning (Shadish, et al., 2002). An experiment generally involves a treatment group that receive an intervention and a control group that does not. The counterfactual reasoning is to compare what happened between the two groups. If there is any difference in outcomes between the treatment group and control group, the effect is evident. Finally, a causal relationship is to prove that the cause and effect are related. The cause must precede the effect. There should not be any confounding factors affecting the effect other than the cause. A simple correlation between the cause and the effect is not sufficient to demonstrate the causal relationship (Shadish, et al., 2002). A. Compare and contrast the distinguishing elements of each of these four designs. a. Experimental designs The key purpose of experimental designs is to test causal hypotheses. There are three requirements: introduction of an intervention (treatment), manipulation (control), and random assignment (Alferes, 2012; Levin, 1999; Shadish, et al., 2002). An intervention is presented to a treatment group. In order to evaluate its effect, a control group is assigned without an intervention. The treatment group and the control group are randomly assigned. One of the distinguishing elements of experimental designs compared to quasi- or non-experimental designs is the use of random assignment (Shadish, et al., 2002). For instance, a pre-posttest quasi-experimental design has a treatment grou... ... middle of paper ... ...s with longitudinal panel designs because both involve multiple observations on the same variable and the same subject over time. In regard to this issue, Deschenes (1990) highlights that a time series design contains more periodical intervals such as weekly, monthly, or yearly. Furthermore, Menard (2002) addresses that a time series design includes “relatively long time series for a single case at a time” (p. 67). Meanwhile, Shadish, et al. (2002) mentions although approximately 100 observations are preferable for causal inference in time-series designs, a small number of observations would also be useful if extra pre- or posttests or control groups are introduced. In addition, I agree with the notion that when a research interest includes patterns of change in a case rather than changes in an individual, a time-series design is more appropriate (Menard, 2002).

Open Document