Based on a twitter query about start-up sizes, I found myself wondering whether the size of a professor's start up package has a measurable effect on their subsequent grant writing success. In particular, do people who get larger start-up packages then get more money, representing a larger return on the larger investment? I designed a brief 5-question survey on google forms, advertised it on twitter, and got 65 responses. This blog post is a brief summary of the results, which surprised me only somewhat.
First off, a brief summary of who replied:
I then wondered whether initial start-up package size depends on gender or the university type, and found a clear and expected result: R1 universities have larger start-up packages. Encouragingly, with this small self-reported sample size there was no sign of a gender bias:
I'd show you the statistical results, but they just obviously match the visuals above.
Subject matter had no significant effect on start-up package size (mostly ecology versus evolution).
Now for the big reveal: does initial start up package size matter for later grant income?
Using the first five years as a focus, the answer is...
no, once you account for university type.
Black dots in the figure are R1 universities, green are non-R1 universities, yellow are private colleges, blue is other. There's no significant trend within either of the well-represented categories (R1, non-R1). If we do a single model with grant income as a function of university type and start-up, only university type is significant. The pattern after 10 years is even stranger:
In both cases it is certainly clear that (1) there's a lot of noise, and (2) people who get start-up packages in excess of about 400,000 do seem to have an advantage at getting more grant money. After 10 years people who got more than 400,000 in start-up all had at least 2 million in grant intake. That seems like a good return on investment. But more is not all better: the biggest grant recipients were middle-of-the-road start-up recipients. Note that gender had no detectable effect in the trend above, but sample sizes were low and the data self-reported.
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