There are many reasons to write a grant, and many places to apply for one – from small grants for a few thousand dollars, to multi-year grants for many millions of dollars. If your grant involves any sort of data analysis or data collection, even something very simple, it can be worth your while to consult with a statistician. It is better to consult early in the process. Although consulting costs money in the short term, it can save you a lot of time and money in the long term, and can improve your chances of getting a grant.
Some ways a statistician can help a grant writer -
1) Finding instruments – not all statisticians can do this, but many (including myself) can. There are a huge array of psychological instruments out there.
2) Making data collection appropriate – when people come to me with data, it’s often collected in ways that make it hard to analyze. Then I spend hours manipulating the data into the proper format. If they had come to me before starting, it would have taken me a lot less time to show them a better way.
3) Power analysis. Many federal agencies such as the National Institute of Health actually require power analysis. Even if you aren’t required to do one, it can be very helpful to do so – to see how many subjects you will need to detect various effects.
4) Analysis plan. If you come to the statistician (such as me) early, then he or she or I can help you answer the questions you want to ask, rather than the questions that the statistical techniques you are familiar with can answer. There is a wide range of statistical techniques out there, and it’s better to let the substantive questions drive the analysis then the other way round. A good carpenter has a big set of tools; but if you are not a carpenter, you may only have a few.
5) Doing the actual analysis – Once you get your grant, and start collecting data, you’ll want to analyze it. A good statistician can do it accurately and quickly, and show you the results in ways you understand
Specialties: Regression, logistic regression, cluster analysis, statistical graphics, quantile regression.