mdmc

Can anyone provide suggestions on mid-range (not top tier, but still solid and respectable) PhD programs in applied stats and/or biostats, especially any with a reasonably strong emphasis on spatial analyses/multilevel/clustered data, etc. ?

Thanks for the input. Many schools (even decent ones) do say that they will consider students who have gaps in their training and possibly admit them on the condition that they make up whatever deficiencies they have. And herein lies the rub: on paper, my math training is next to nothing, but for many of the places I've looked into, I can easily do the things on their self-check lists. For example, Johns Hopkins says that you should be able to do the following: Perform algebraic manipulations. Graph an exponential function. Find values that minimize a function by setting the first derivatives equal to zero. Perform an integration. Find the product of AB where A is a 2x3 matrix and B is a 3x2 matrix. I've had two sequences of calculus and am working through a book on calculus III, know the basics of diff eq, have had a probabilities course, and remember the basics of linear algebra. Also, for many of these programs, I have already taken a large portion of the required coursework. I was hoping that would make my application a little more competitive. But perhaps not? How much does it really come down to how much math my transcript says I can do? The subject test is out of the question this late in the year, and waiting another year would be rough, as that would put me a good way into my sociology dissertation (at which point I might as well stay where I am).

I am currently a sociology PhD student (undergrad: soc and pol. science, master's soc) and am planning out applications for a switch to applied stats/biostats. Unfortunately, I'm new to the field so I'm having a hard time figuring out where I stand and how good of a shot I have. My sociology work has been fairly quantitative but my actual math training is a little weak. I could really use some insight about programs I should be looking into and my chances of getting in. Here's some of my info: GRE quant: 740 Undergrad gpa: 3.89; Grad gpa: 3.91 Highest "Formal" math training: AP calc in high school; am reasonably competent (through independent study) in most of the standard prerequisites, but might need a bit of a refresher (perhaps probationary admission?) Coursework taken on: basic/descriptive stats, anova, regression, generalized linear models, categorical data analysis, multilevel modeling, structural equation modeling, some IRT I'm learning C/C++ Programs I'm looking at (maybe too ambitious?): Duke, Ohio State, Minnesota, WashU, Johns Hopkins, University of Michigan, Rice, UNC, University of Iowa, Rutgers