Basic designs, corresponding questions, analytical methods

Basic Designs, Corresponding Questions, Analytical Methods, and Limits on Implications of Findings Basic Designs Research designs are the plans or blueprints that researchers use to collect and analyze data. The design of a study is determined by the research question that the investigator is trying to answer. Some common research designs include:

• Experimental designs: Experimental designs are used to test the cause-and-effect relationship between two or more variables. In an experimental design, the investigator randomly assigns participants to either a treatment group or a control group. The treatment group receives the intervention that the investigator is interested in studying, while the control group does not. The investigator then compares the outcomes of the two groups to see if the intervention had an effect.
• Quasi-experimental designs: Quasi-experimental designs are similar to experimental designs, but they do not involve random assignment. This can be because it is not possible to randomly assign participants in certain settings, such as schools or hospitals. In a quasi-experimental design, the investigator may compare the outcomes of two groups that are similar in all other respects, except for the intervention that the investigator is interested in studying.
• Observational designs: Observational designs are used to study the relationships between variables without trying to change or manipulate them. In an observational design, the investigator simply collects data on participants and observes what happens. Observational designs can be used to identify risk factors for disease, to study the natural course of a disease, or to evaluate the effectiveness of a treatment.

Corresponding Questions The type of research question that a researcher is trying to answer will determine the best research design to use. For example, if a researcher is interested in studying the causal relationship between smoking and lung cancer, they would need to use an experimental design. However, if a researcher is interested in studying the risk factors for heart disease, they could use an observational design. Analytical Methods The analytical methods that a researcher uses will depend on the type of research design they used and the type of data they collected. For example, in an experimental design, the researcher might use a statistical test to compare the outcomes of the treatment group and the control group. In an observational design, the researcher might use a statistical test to identify relationships between variables. Limits on Implications of Findings It is important to note that no research design is perfect. Each design has its own strengths and weaknesses. Additionally, the implications of research findings are always limited by the quality of the data and the methods used to analyze the data. One important limitation is that observational studies cannot prove causation. Observational studies can only identify relationships between variables. It is possible that a third variable is causing the relationship between the two variables that the researcher is interested in. Another limitation is that research findings are always specific to the population that was studied. It is not possible to generalize the findings of one study to a different population. Example Here is an example of a research question, corresponding design, analytical methods, and limits on implications of findings: Research question: What is the effect of a new drug on the survival of patients with advanced lung cancer? Corresponding design: Experimental design Analytical methods: Statistical test to compare the survival of the treatment group (patients who receive the new drug) and the control group (patients who do not receive the new drug) Limits on implications of findings: The study results can only be generalized to patients with advanced lung cancer who are similar to the participants in the study. Additionally, the study cannot prove that the new drug caused the improvement in survival. It is possible that another factor, such as other medications that the patients were taking, caused the improvement in survival. Conclusion Research designs are essential for conducting high-quality research. By understanding the different types of research designs and their strengths and weaknesses, researchers can choose the best design for their study and collect data that will answer their research question.  

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