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Jon Peck

Bayesian Blog

I have posted a blog item about the seven new Bayesian procedures in SPSS Statistics 25 here for those who are interested.

https://wp.me/p60OQX-1O0

Jon K Peck
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Kornbrot, Diana

Bates procedures

Dear Jon

that is really helpful

have some additional potentially useful suggestions and would like opinion of SPSS community

GeneraliZed linear models provides BIC.

So why not use it for Bayes FACTOR?

Run both with and without the tested predictor and take the ratio (BIC with predictor)/(BICwithout predictor).

this seems to me simple and direct. Where is the flaw?

Meanwhile, I note that GeneraliZed linear MIXED gives F-tests for predictor BUT GeneraliZed linear gives chi-square tests [Wald or likelihood]. Why is that? completely mystified.

Both provide BIC, values close but not identical

best

Diana

On 18 Aug 2017, at 21:49, Jon Peck <[hidden email]> wrote:

I have posted a blog item about the seven new Bayesian procedures in SPSS Statistics 25 here for those who are interested.

https://wp.me/p60OQX-1O0

--

Jon K Peck
[hidden email]

===================== To manage your subscription to SPSSX-L, send a message to [hidden email] (not to SPSSX-L), with no body text except the command. To leave the list, send the command SIGNOFF SPSSX-L For a list of commands to manage subscriptions, send the command INFO REFCARD

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Rich Ulrich

Re: Bates procedures

I don't remember if I ever used BIC or AIC in anything published, so I'm not the best

possible reference here. But I don't see anybody's response.

There are two formulas for BIC - one for maximum likelihood solutions and the other

for ANOVA (least squares). When the different criteria don't reduce to the same thing,

the solutions will be slightly different. I'm not sure what you are looking at, but it is

certainly possible to compute BIC in both ways on one set of data.

As I understand it, and the Wiki page seems to support it, BICs are compared by their

difference, not the ratio. I think of it as approximating a 1 d.f. chi-squared.