#1 cause for OpenMx model results that are obviously wrong

Sarah pedland at ITW2014 shared this piece of wisdom - If your model results seem massively wrong, the first thing you should check is how your dataset is arranged. If you have variables in rows, and participate cases in columns, then that's the culprit. You must arrange your variables in columns and cases in rows. This dataset error is the cause more than 90% of the time!