Dear all,
with respect to detecting outliers, the STATA manual (R: regression diagnostics) says that following Belsley, Kuh and Welsch (1980), observations with DFITS values greater than 2*sqrt(k/n) deserve further attention, where k is the number of estimated coefficients and n is sample size. However, I have sometimes seen people stating that it is the absolute value of DFITS that matters, such that observations with abs(DFITS)>2*sqrt(k/n) deserve further attention. In many estimations, I get observations with a negative DFITS, so which formula is correct matters. Not having access to Belsley, Kuh and Welsch (1980) myself, I wonder whether anybody can shed light on this? Many thanks, Eric Neumayer
Dr. Eric Neumayer
Lecturer in Environment & Development
London School of Economics (LSE)
Department of Geography and Environment, Room S416
Houghton Street
London WC2A 2AE
+44-20-7955-7598 (phone)
+44-20-7955-7412 (fax)
Email: [email protected]
Website: http://www.lse.ac.uk/Depts/geography/Eric1.htm
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