I'm a newb here, so I'm not sure how the activity in the forum is moderated. I assume I'm allowed to post questions here relative to the topics in the course videos. That said, I recently completed "Managing in-vivo Studies" and had two questions:
- The slide shown at 02:00 mentioned "research model" in the last bullet. I may have missed it, but it's unclear to me what a research model is. Are there different types of research models? What thought process does one apply to decide what research model to use?
- The slide shown at 14:10 mentions pitfalls. If I am a novice and approach a lab to do animal testing, generally speaking, will that lab help me pinpoint potential pitfalls before diving into the work? Or will they leave me clueless and just run the study, no matter how many pitfalls they may see, thus wasting my money?
Thanks in advance!
Research Models are very generally described as either quantitative or qualitative. Quantitative models are normally compact representations where a single differential equation can describe system performance regarding a large set of input functions and initial parameters (usually portrayed in a numerical sense). Qualitative models position descriptive entities within a metric frame, following either a set-theoretic approach or a logical one.
Some common pitfalls or areas for error are as followed:
- Over generalizing your results resulting in generalizations of subjects based solely on a few interviews, observations, or surveys.
- Biased methodology and questions that foster the prevalence of biased results.
- Assumption of correlation as means of causation (a relationship between terms of observation doesn't not mean on causes the other). This can also cause other related factors to be neglected.
During your academic studies or research, have you encountered some research pitfalls? If so how did you and your team address this? Could these pitfalls have been avoided?
Source:
Clark, M. P., Slater, A. G., Rupp, D. E., Woods, R. A., Vrugt, J. A., Gupta, H. V., ... & Hay, L. E. (2008). Framework for Understanding Structural Errors (FUSE): A modular framework to diagnose differences between hydrological models. Water Resources Research, 44(12)
Hey @m_ridzon I like the questions you asked as I also had questions like yours prior working in research.
I do not fully agree with @jadebowale said about what research models are when Professor Simon mentioned them in his lecture. Rather than being quantitative or qualitative I believe the professor was referring research models to what animal model was being considered for the research. When posing a question it is a critical question to ask of which animal species should be used for the research. Some animal models are considered the industry standard when conducting a specific study. For example, chinchillas are best known for their auditory research results and are the preferred species for auditory research.
In terms of your question about pitfalls, I can speak from my personal experience about unexpected pitfalls that may occur due to logistical issues. For example, when I was designing my master’s thesis I had to take into account the various devices I would be using and how long I would need to use each device as I had to allow for others to use the device as well. This ended up in me allotting extra time in my plan in case I was not able to meet certain deadlines due to the inability to use the microscopes or cryostat devices. Additionally, certain assays and materials may be too expensive and you may have to search for a cheaper approach to accomplish the same objective that you sought out to investigate.
