Checking in.

[rivka]

I'm back at work for the second day. Yesterday I had an unusually light clinic schedule, so despite some continuing shortness of breath I decided to go in. Then I wound up having to arrange for a patient to be hospitalized, so it wasn't the lightest day after all. I need to call and find out whether he was actually admitted - I walked him over to the ER, and left the kind of note for the ER physician that should always result in admission, but the patient is kind of confused and I suppose that a lazy doc trying to avoid an admission at all costs (it's a lot of extra work) could worm out of him a promise not to kill himself before he sees his outpatient psychiatrist again, and call that justification for sending him home. So we'll see.

I just got off the phone from an hour-long conversation with my dissertation advisor. I sent him a huge number of analyses almost a month ago, and he kept putting off looking at them. I finally cornered him into agreeing to a phone appointment today to discuss them. The good news: he agrees that there really is something there in my results. The bad news: he thinks I need special analytic tools that neither of us really understands. Anyone out there an expert in logit and probit models? How about nonparametric models?

Comments

[rivka.livejournal.com]

My problem is that the data for my principal outcome measure is not even close to being normally distributed: I've got mostly scores of 0, with a scattering of higher-than-zero scores. Obviously this violates the assumptions of most statistical tests - it's not really fair to compare mean scores of my two groups using ANOVA, for example, which sucks because the ANOVA comes out significant. And I can't manage to set up a meaningful regression equation to test the contributions of possible predictors, because the range of the outcome variable is so restricted and the scores are so heavily clustered at zero.

Inspecting the data, it really does seem that a group difference exists. The question is which statistics we can legitimately use to bring it out. I fear that if I just cite the significant ANOVA result I'll be crucified by my committee, and rightfully so. But I don't know how else to organize the data analysis. If your biostatistics guru officemate has good suggestions, I am willing to provide any reasonable sort of reward. (For example, Godiva chocolates.)

[therealjae.livejournal.com]

Get thee to a stats consultant. I'm serious; they're worth the effort I'm sure the U of Maryland has a centre, though you might have to go to College Park.

-J