plm(): observations not used for modelling
On Nov 6, 2012, at 7:55 AM, Daniel Bab. wrote:
Hello, I have posted this problem before, but thought I try to explain it a bit better. I'm using the function plm to create a fixed effects model for panel data, my method is therefor "within" my effect is "twoways". My Data contains unbalanced Panels due to missing Values, but contains 309 observation for 11 variables (incl. response), with no missing Values. These 309 observations distribute over 25 individuals and 18 years. The fuction plm only uses 286 of these observations (also if the model is changed to first differences and the effect to individual) and omits 23 observations due to na.action, but in my dataset they do not contain NAs. Is this due to the Transformation used in the plm function? If it is of any help, these are the observations that are omitted (which obviously don't contain NAs): TIME GEO 98 1993 Deutschland (einschlie?lich der ehemaligen DDR seit 1991) 99 1994 Deutschland (einschlie?lich der ehemaligen DDR seit 1991) 100 1995 Deutschland (einschlie?lich der ehemaligen DDR seit 1991) 101 1996 Deutschland (einschlie?lich der ehemaligen DDR seit 1991) 370 1999 ?sterreich 372 2001 ?sterreich 375 2004 ?sterreich 385 1995 Polen 386 1996 Polen 387 1997 Polen 495 1991 Schweden 439 1992 Slowenien 440 1993 Slowenien 441 1994 Slowenien 442 1995 Slowenien 443 1996 Slowenien 172 1991 Spanien 173 1992 Spanien 174 1993 Spanien 175 1994 Spanien 176 1995 Spanien 177 1996 Spanien 178 1997 Spanien Verkehrstote_Quote Autobahnlaenge_Quote PKW_Quote$Value LKW$Value
I was surprised to a "$" in a variable name. Are you sure that is not the source of your problems?
dat <- data.frame(a$b = 1:3, d=1:3)
Error: unexpected '=' in "dat <- data.frame(a$b =" I would not expect the internal parsing routines to necessarily properly handle invalid column names.
David. > 98 123 0.0310283316 479 19.62343 > 99 121 0.0312047562 489 25.99028 > 100 116 0.0313363746 496 27.16505 > 101 107 0.0314931965 501 27.78134 > 370 135 0.0194823002 502 39.96261 > 372 119 0.0196134540 521 41.26695 > 375 108 0.0199949923 505 40.89616 > 385 179 0.0007867343 195 33.66977 > 386 165 0.0008251115 209 35.50949 > 387 189 0.0008443002 221 36.80187 > 495 87 0.0021512832 421 31.19678 > 439 247 0.0125413519 304 16.00871 > 440 247 0.0132326075 317 17.05044 > 441 254 0.0136769861 330 18.09584 > 442 209 0.0144669925 351 20.10579 > 443 195 0.0153063744 366 21.10271 > 172 227 0.0103736290 322 110.86938 > 173 200 0.0128525994 336 67.96822 > 174 163 0.0130329241 343 69.89171 > 175 143 0.0128743969 350 72.00581 > 176 146 0.0137958367 361 74.65096 > 177 139 0.0144557065 374 77.52797 > 178 142 0.0153573304 387 81.11232 > Motorraeder$Value Bevoelkerungsquote Quote_Jung Quote_Alt > 98 19.561682 226.76063 12.31254 3.928754 > 99 23.297817 227.77846 11.82362 4.011330 > 100 27.802782 228.33996 11.40332 4.087582 > 101 30.189141 229.12098 11.19176 4.026278 > 370 32.947233 95.17546 11.98196 3.378319 > 372 36.778704 95.63432 11.90409 3.558421 > 375 38.808372 97.08449 12.20926 4.066773 > 385 24.079461 123.38487 15.48095 2.154967 > 386 22.688776 123.47698 15.82873 2.102519 > 387 21.791262 123.57274 16.09662 2.027340 > 495 5.238265 19.09182 13.55292 4.302106 > 439 5.502994 98.69708 14.60535 2.364486 > 440 5.516317 98.45870 14.58509 2.464340 > 441 4.523959 98.22782 14.64697 2.535880 > 442 4.523802 98.23123 14.74327 2.612043 > 443 4.019563 98.27018 14.93248 2.567195 > 172 30.199689 77.03350 16.89450 2.962978 > 173 32.074025 77.28903 16.86363 3.062267 > 174 32.684277 77.54355 16.80052 3.163572 > 175 32.817935 77.77117 16.69243 3.261328 > 176 33.068060 77.96193 16.53155 3.352908 > 177 33.171926 78.13598 16.31481 3.438006 > 178 33.548015 78.32325 16.02780 3.510471 > Quote_Erstzulassungen BIP$Value Alkohol.Wert > 98 0.09782568 21100 13.50 > 99 0.08070474 22200 13.37 > 100 0.08202309 23600 13.35 > 101 0.08530314 23400 13.12 > 370 0.07834963 24900 13.40 > 372 0.07018843 26600 12.80 > 375 0.07575858 28700 12.50 > 385 0.05996661 2800 8.14 > 386 0.07789285 3200 8.08 > 387 0.08464139 3600 8.64 > 495 0.05298563 24200 6.28 > 439 0.05147030 4800 13.64 > 440 0.09212000 5400 14.31 > 441 0.07068413 6100 13.38 > 442 0.08677918 8100 13.36 > 443 0.07988964 8400 12.04 > 172 0.07290907 11400 13.23 > 173 0.07695772 11800 12.50 > 174 0.05522833 10800 12.03 > 175 0.06836836 10800 11.70 > 176 0.06125084 11600 11.38 > 177 0.06563393 12400 11.07 > 178 0.07133359 12800 11.95 > > TIME and GEO are the Index of my Paneldata, "Verkehrstoten_Quote" is the > dependent, all others the independent variables. > If anyone could help me understand, why these observations (or generally > any) are left out, I would be very glad. > > Thank you for dealing with my Problem. > Regards, > Daniel > > > > -- > View this message in context: http://r.789695.n4.nabble.com/plm-observations-not-used-for-modelling-tp4648571.html > Sent from the R help mailing list archive at Nabble.com. > > ______________________________________________ > R-help at r-project.org mailing list > https://stat.ethz.ch/mailman/listinfo/r-help > PLEASE do read the posting guide http://www.R-project.org/posting-guide.html > and provide commented, minimal, self-contained, reproducible code. David Winsemius, MD Alameda, CA, USA