What are the steps to selecting a research methodology?

1. Define the scope and objectives of the research. 2. Structure the plan and find resources to conduct research. 3. Choose the appropriate type of research methodology based on the objectives of the?research. The methodology could be qualitative or quantitative research. 4. Decide whether to use primary or secondary research data. If you want to analyze a large amount of readily available data, use secondary data. If you want data specific to your purposes with control over how it is generated, collect primary data. 5. Choose the appropriate research method based on the type of research methodology you have selected.

The research methodology selection process is a crucial step in the research process, involving defining the problem, reviewing existing literature, understanding the philosophical approach, determining the research nature, choosing quantitative or qualitative methods, considering time and resource constraints, and accounting for ethical considerations. It involves pilot testing, consulting experts, iteration, considering the analytical framework, evaluating generalizability, documenting the methodology, and periodically reflecting on the chosen methodology. Flexibility is key.

One thing I found helpful in selecting a research question is to first choose a general topic such as protein synthesis or deficiency, break it down to minor topics and methodologies ie crispr cas and remember, be prepared to pivot.

Defining the research topics and clear objective is the start of a good quality paper. First, selecting an original topics would increase the chance to get published. Second, stating clearly the objective of the study would facilitate the elaboration of research questions. However, researcher, especially in the field of development economics and agricultural economics, need to be careful when generating their research questions. In my experiences, it is really important to propose feasible research questions. I remember that during Covid-19 it was really challenging to get primary data. Thus, I needed to adapt my research questions based on the secondary data available.

"Understanding" your research question is the correct term, I believe. What I believe most of the budding PhD students or scientists lack is that they start to think only technically, without trying to decode their intention of that particular project! Once you understand what you intend to explore in your thesis, then it becomes clear as to what you need to experimentally set up. Only then the other statements such as "define" your research will make sense.

To quote a former professor of mine who taught me: methods of culturing microbes in the lab, make your life easier in the lab and your scientific writeup. Use ai amongst the tools of data collection for comparison analysis and differentiation of data to come up with the best optimal result.

Performing literature review is one of the most important step when selecting research methodology. It allows researcher to know and understand what is already done in the field. When I start research, I like to refer to the articles published in top journals. I believe that these are high-quality research that would help me to improve my skills.

With time, the quantity of papers published from a group surpassing the quality. Due to this reason, there are always two sides to a story and it is difficult for the student to choose an appropriate research question, to find support or relevance. Therefore it is important to include literature from at least two decades to understand the background of the story and then to continue with the latest publications to understand the contradictions and significance. This helps the students to identify the research gaps and helps them to choose a right path of hypothesis and experimental set up.

When choosing a research design, researchers must also consider practical constraints, ethical considerations, and the available resources. The selected design should align with the research goals and provide a robust framework for data collection and analysis. Additionally, it's crucial to stay open to adjustments during the research process if unforeseen challenges or opportunities arise.

One thing I've learnt about this part is It doesn't usually hurt to over budget for this especially if it entails paying fees to patients who are either participating in a pre clinical or post clinical trial.

In my experience, it is useful to have a data analysis plan (DAP) with core indicators and planned disaggregation prior to receiving the data. The DAP can be developed in parallel with the questionnaires and surveys. That should be the baseline. Yet, during data analysis it can be expanded, indicators and results can be triangulated and/or aggregated, new composite indicators could be created ad-hoc. Ideally, data analysis should be conducted with two objectives in mind: identifying the most relevant information to provide the audience with, and understand how to present them in a clear and concise format. Depending on the audience, a million indicators may not have the same effect of a well-structured composite indicator or index.

Many times I see that the scientists evaluate their data by themselves or within their group, trying to make sense out of the data accumulated over the years. From my own experience, I learnt that collaborating with other groups to evaluate data will bring out surprising and interesting results. So I suggest maintaining corporations between cross functional teams not just to experiments but until data analysis and evaluations.

Research in social sciences is often costly. In most of the time, researcher in this field needs good quality data from the field to complete the work. However, data availability should not be an issue for researcher. There are several methodology that would not require primary data collection citing only game theory approaches. Moreover, with the advancement of technology, there is now several open sources data that can be used for the research. I believe that these data are worth to use and can be a valuable tools for a good quality research to increase the number of works in the field of agricultural economic and economic development.