1. I really like the word “toast.” I also really like toasters. Especially brave ones.
2. Yay, I can still run 10k in under an hour, even after not running since August!
3. I found the perfect job for me. Unfortunately, it’s at Twitter and I don’t know if I could go on living with myself if I worked for Twitter. Google, maybe (ASSIMILATION). Twitter? No.
Another goal I want to add to my New Year’s Resolution list is this: I want to try and make some progress on a new SEM fit index, one that works better overall than the current popular ones. While I don’t think we’ll ever arrive at an index that is as error free as we’re hoping to find, I think there is currently still a lot of room for improvement.
For example, the CFI works very well for detecting discrepancies between the model and the actual data when the discrepancies are at the latent level (e.g., the researcher’s model proposes two latent variables but the model underlying the actual data in reality has three) but does horribly at properly reflecting the degree of misspecification when there are error covariances omitted from a model (CFI shows excellent fit when the omitted error covariance is low or very high; it shows terrible fit when the omission is moderate in size).
I thought I had this super awesome idea the other day to apply a sort of bootstrapping mechanism to act as a fit index, but that’s already been thought up and either a) doesn’t work very well or b) is very hard to implement, as there are several papers on a bootstrap-like fit index but little documentation of the use of it (I didn’t come across it at all during my lit reviews). So maybe I’ll do some more research into that…perhaps my idea of how bootstrapping should be implemented in assessing fit is different (and probably way more incorrect…but whatever).
There are also transformations to look at, too, which would require examining how the minimum fit function changes as the size of the misspecification (as well as the TYPE of misspecification) changes.
You know what all this means? PARTY TIME WITH R!
I might as well be dating it, it’s not like I’ll ever have a boyfriend again.
But that’s okay. R!