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| From | "Martin Weiss" <martin.weiss1@gmx.de> |
| To | <statalist@hsphsun2.harvard.edu> |
| Subject | st: AW: RE: AW: correlate lag variables |
| Date | Mon, 10 May 2010 18:54:13 +0200 |
<> " I'm coning into this a little late, but did anyone notice that when you include lag 2 you have 225 observations and when you include only lag 1, you have 265. " That resembles Nick`s point in http://www.stata.com/statalist/archive/2010-05/msg00471.html closely, I would say. HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Lachenbruch, Peter Gesendet: Montag, 10. Mai 2010 18:51 An: 'statalist@hsphsun2.harvard.edu' Betreff: st: RE: AW: correlate lag variables I'm coning into this a little late, but did anyone notice that when you include lag 2 you have 225 observations and when you include only lag 1, you have 265. Setting es=e(sample) after the lag 2 analysis and rerunning the correlation for lag 1 if es==1 might shed some light on the problem. Tony Peter A. Lachenbruch Department of Public Health Oregon State University Corvallis, OR 97330 Phone: 541-737-3832 FAX: 541-737-4001 -----Original Message----- From: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] On Behalf Of Martin Weiss Sent: Monday, May 10, 2010 1:24 AM To: statalist@hsphsun2.harvard.edu Subject: st: AW: correlate lag variables <> Try -pwcorr- instead: ************* clear* set obs 100 gen y=1 replace y =.6*y[_n-1]+rnormal() in 2/l gen byte time=_n tsset time corr y L.y L2.y pwcorr y L.y pwcorr y L.y L2.y ************* HTH Martin -----Ursprüngliche Nachricht----- Von: owner-statalist@hsphsun2.harvard.edu [mailto:owner-statalist@hsphsun2.harvard.edu] Im Auftrag von Julia Gesendet: Montag, 10. Mai 2010 10:17 An: statalist@hsphsun2.harvard.edu Betreff: st: correlate lag variables Dear all, I would like to calculate the correlation between a variable and its past values. Thus, I use the following command: . correlate BI L1.BI L2.BI (obs=225) | L. L2. | BI BI BI -------------+--------------------------- BI| --. | 1.0000 L1. | 0.0111 1.0000 L2. | 0.0647 0.0161 1.0000 However, if I only ask the correlation for the first lag, my result differs.... . correlate BI L1.BI (obs=265) | L. | BI BI -------------+------------------ BI| --. | 1.0000 L1. | 0.0174 1.0000 Why does excluding the second lag affect the correlation between the variable and its first lag? Best regards, Julia * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/ * * For searches and help try: * http://www.stata.com/help.cgi?search * http://www.stata.com/support/statalist/faq * http://www.ats.ucla.edu/stat/stata/