Thursday, 17 May 2018

Reading Assignment - Grant Applications

The purpose of this reading assignment is to give you a sense of the sort of things that someone consulting a statistician will want to know.

Read Chapter 22 – Writing the Data Analysis Plan, by A.T. Panter, of the book How to Write a Successful Research Grant Application – A Guide for Social and Behavioral Scientists, Eds.
Pequegnat et al., 2nd ed., and answer the questions that appear after the preliminary notes.
 

Note that this book is directed toward researchers in the social sciences, and this chapter is about the sort of questions to ask of a statistics expert. The book is written with the national granting bodies of the United States in mind, but a lot of the material, including the data analysis chapters, is relevant to grant applications to bodies in other countries such as Canada’s NSERC and SSHRC.

Before reading the chapter, know these definitions:

Grant: An amount of money awarded to a university or organization in order to do a proposed research project. Typically a competition is run for grants, in which a certain number of grants meant to advance research in a particular field or towards a particular goal are available, and researchers need to submit applications for these grants. In most cases, there are more applicants than grants available.

Granting body: An organization that awards grants. These include government bodies like NIH in the United States or NSERC in Canada, but a non-government organization like the Bill and Melinda Gates Foundation can also award grants.

Principal Investigator (PI): The person whom will be in charge of the proposed research. Also the person who actually submits the grant application. Typically this is the most qualified person on a research team. Every other researcher on the team is a co-investigator.

Reviewer: Person who reads grants applications and assigns scores to them based on their merit and relevance to the goal of the competition. Typically an application will be seen by several reviewers and an aggregate score is given.

Be sure to write the answers in your own words; they don’t have to be long.
Q1. What are three things that grant applicants must demonstrate to reviewers that they are able to do?

Q2. What is an advantage of thinking about your data analysis plan when doing a grant application?

Q3. What is one way to use the scores of many closely related variables or items together?

Q4. What is the main advantage of using a known measure over creating a new one?

Q5. What are two reasons why you would make a new scale, rather than rely on one in the literature?

Q6. What are three of the possible roles that a variable can have?

Q7. Name three of the special features of a research design. For each feature, name something that you should study or know about before using each of those features.

Q8. What is something that should be included in a descriptive analysis?

Q9. What is a question to ask yourself during model development?

Q10. How much of a grant application should be allocated to the data analysis plan?


This is just one of the 20 such reading assignments that will be included with answers in my upcoming book Writing for Statisticians, soon to be available at TopHat Marketplace.