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Go to options>worksheet then increase worksheet size to a large amount (experiment)

Yes. But depends of course on the spec of your computer. See 'How do I know MLwiN can handle the model based on my own data?' (http://www.cmm.bristol.ac.uk/MLwiN/tech ... html#capac)

You can check whether the entire dataset has been imported properly by comparing the summary statistics: are they the same in MLwiN as in your other stats package

Try using a random sub-sample of your data. With only 2 levels, 700 level 2 units and 10 covariates you do not need nearly as many as 250000 observations to get precise estimates. You will be able to work a lot more quickly with a smaller sample and therefore be able to explore more avenues and ...

I would suggest importing a subset of your data, eg, a random sub sample of your higher level units. Even if you manage to get all the data in all but the simplest models would take a very long time to converge. A side benefit of using a sub-sample of data will be that you can check that you haven't ...

Although it appears that only 5 variables are being exported when you use the ASCII text file output window from the File menu, in fact all 10 are exported. However you only see 5 columns of data because when you export more than 5 columns MLwiN wraps the data - see section 2 of Getting data out of ...

No, MLwiN should count '__ABC' and 'ABC' as different. To test whether MLwiN considers 2 names to be the same, open MLwiN without opening any worksheet (you can do this via the Programs menu, via a shortcut, or by clicking on MLwiN in its folder in your Program files, or alternatively you can double ...

This error message will be produced if there are two variables with the same name in the Stata file you are trying to open. Note that MLwiN does not distinguish between small and capital letters, so for example variable1, Variable1 and VARIABLE1 will all be considered the same name. Inside Stata ...

When you enter a categorical variable as an explanatory variable (or as the response of a multinomial model), MLwiN will enter in all the categories of the explanatory variable even if some categories have no observations. The situation where some categories of a variable have no observations may ...

If you have any categorical variables for which there are no observations in some of the categories, see 'How do I get rid of an unneeded dummy variable?' below