Hi community,

To analyse my data, a multivariate probit model is suggested in the literature. I have six dependent variables and up to 7 independent variables. I have already coded the data in Excel and then read it into R for the analysis. At first I got no output at all, but in the meantime I managed to get something. Unfortunately, the following error message appears at the end and the data are not comprehensible:

When I enter warnings(), the same error message always comes up, namely:

The correlation matrix is not positive definite

and this many more times.

I don't quite understand it, because I did it the same way as in the paper "What hampers innovation? Revealed barriers versus deterring barriers" by D'Este et al. (2012).

ChatGPT couldn't help me any more either.

This is the code I need for the model:

model.MVP2 <- mvProbit(cbind(Cost.B, Knowledge.B, Market.B, Regulation.B, Data.B, Trust.B) ~ Little + Average + High + Very_High + LN_Employees + Higher_Education + RD_Invest, data = data)

summary(model.MVP2)

The data are all binary coded except for "LN_Employees + Higher_Education + RD_Invest", but this should not be a problem.

Can someone help me? I'd be very thankfull.