V gone -ve definite for block 0 iteration aborted (random pass, offsets 1)

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HALIMIMY
Posts: 1
Joined: Tue Mar 19, 2019 4:00 pm

V gone -ve definite for block 0 iteration aborted (random pass, offsets 1)

Post by HALIMIMY » Tue Mar 19, 2019 4:22 pm

Dear community,

I ran into trouble trying to model the following model in mlwin (version 3.03):

In the model we would like to estimate chances of persisting in an educational programme. So, our dependent variable is chance of persistence, which is measured as a continuous variable (0 - 10). However, the data collection was designed as a factorial survey, that is, we used vignettes to measure students' chances of persistence under variable circumstances. More specifically, students were asked to rate 6 vignettes whichvaried along two dimensions (one dimension being study success [categorical] and a second dimension being study progress requirements [yes/no]). About 500 students rated all vignettes, meaning we have a sample of about 2900 observations (of persistence chances).

The study is mutilevel by design, that is to say, we assume that the variance in persistence chances is partially on the level of the vignettes (Level 1) and partially on the level of the student (Level 2).

We already ran into problems, while defining the 0-model only taking into account the first level.
The problem was the following; V gone -ve definite for block 0 iteration aborted (random pass, offsets 1), which resulted in a 'numerical error calculating likelihood' (see attachments).

Can anyone advise us on the underlying problem and/or how to go about this?

Many thanks,
H.
Attachments
Error output.PNG
Error output.PNG (15.16 KiB) Viewed 35 times
Knipsel.PNG
Knipsel.PNG (11.67 KiB) Viewed 35 times

ChrisCharlton
Posts: 1067
Joined: Mon Oct 19, 2009 10:34 am

Re: V gone -ve definite for block 0 iteration aborted (random pass, offsets 1)

Post by ChrisCharlton » Wed Mar 20, 2019 6:01 pm

I am not sure what would cause this. As this model is equivalent to a regression with only an intercept have you tried fitting this model with other software to ensure that the results look sensible there?

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