Hi,
I'm conducting a multinomial logistic regression on some British Crime Survey data. For this analysis I need to weight the dataset in order to account for sampling biases.
The problem I'm having is when I apply the correct weight and run the multinomial regression, my model fitting criteria for the model fitting information and likelihood ratio test come up with a blank (...). As a consequence, everything in my model is coming out as significant, which I know is wrong.
I have run the model before using a different weight, which I now know is wrong for use in my particular analysis, so I believe there is a problem with this new weighting, rather than any of the other inputs into the model.
Has anybody else had experience of this? If it's a problem with the weighting is there anything I can do to fix it?
Any help would be very much appreciated!
I'm conducting a multinomial logistic regression on some British Crime Survey data. For this analysis I need to weight the dataset in order to account for sampling biases.
The problem I'm having is when I apply the correct weight and run the multinomial regression, my model fitting criteria for the model fitting information and likelihood ratio test come up with a blank (...). As a consequence, everything in my model is coming out as significant, which I know is wrong.
I have run the model before using a different weight, which I now know is wrong for use in my particular analysis, so I believe there is a problem with this new weighting, rather than any of the other inputs into the model.
Has anybody else had experience of this? If it's a problem with the weighting is there anything I can do to fix it?
Any help would be very much appreciated!