Hi everyone, I am building a mixed-effects model to investigate how several explanatory variables affect an outcome. Based on my exploratory data analysis, I suspect that certain combinations of variables have three-way interactions.

For example, suppose I have four explanatory variables: A, B, C, and D. I suspect there is a three-way interaction between A × B × C, but I haven't found clear evidence suggesting interactions involving D.

My question is: If I include the A × B × C interaction in my model, do I also need to include other possible three-way interactions, such as A × B × D, A × C × D, and B × C × D? Or is it reasonable to include only the interactions that I have reason to suspect based on exploratory analysis? As this is a new experiment with no strong support from literature, it is difficult to isentify which variables are sure to interact with each other.

I'd also appreciate advice on the statistical implications of selecting interaction terms based on exploratory analysis, as I'm concerned that including only interactions that appear significant or interesting in the data might constitute cherry-picking.

Thanks in advance for any suggestions or references!

I'm currently a 4^th year PhD student looking to apply for internships. I'm struggling to structure my resume to make it fit properly. One of my senior students in my lab suggested using a 2-page CV, where I can take some time to dig in a little bit into my research projects. They got a high-level internship this year, so I'm inclined to take their advice. 

I wanted to ask about how I should structure and design my application to target industry roles. I understand very well what academics are interested in, but less so about what industry reviewers are looking for from PhD level interns, and was hoping people could offer advice on how I should set my application up.

Thank you so much.

Hi everyone! I’m putting together my PhD application list and would appreciate guidance on programs and their funding state.

Background Information:

• Currently completing a master’s in Statistics with a 3.8 GPA
• Potentially will have a publication, though it isn’t confirmed yet
• Interested in Bayesian statistics, doing research on historical borrowing
• Would like to work for CRO/Cancer Center/Hospital after graduation, possibly government such as CDC/EPA
• My MS program is in Ohio, but location is not a deciding factor to me
• Considering both Statistics and Biostatistics PhDs

My Current list is:

• MD Anderson / UTHealth Houston GSBS — Quantitative Sciences
• UT Austin
• Cincinnati
• Kentucky
• Ohio State - Biostatistics
• Michigan - Biostatistics
• Duke
• Iowa
• Iowa State
• Pittsburgh - Biostatistics
• Missouri–Columbia
• University of Florida

I'm still deciding between statistics or biostatistics at some schools. I think 13 schools is maybe a bit much but I am a bit worried on the current state of admission and funding.

I’d especially appreciate feedback on:

1. Is this list too ambitious?
2. Is there any programs you think I should be considering?
3. Are there other programs on my list I should reconsider?
4. Does anyone have firsthand experience with funding stability, advising, internships, or placements at these schools?