[Rasch] Rasch and Missing data
luckyantonio2003 at yahoo.com
Sat Jul 5 02:25:41 EST 2008
It is generally argued that RM is robust to missing data because the total score is the sufficient statistic for parameter estimation.
But, missing data affects total score too. Suppose that in a complete data set the total score of a person is 25 out of 30. If this dataset is affected by ‘missingness’ then the total score of this person would be say, 21 out of 30. If his measure when there’s no missing data is say, 2 logits (based on 25/30) his measure from the ‘missingness struck’ dataset would be say, 1.5 logits because some of his correct answers are missing and his raw score diminishes (21/30). So the measure we get is not equivalent to what we would have got when all data were present.
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