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 (einschließlich der ehemaligen DDR seit 1991) > 99 1994 Deutschland (einschließlich der ehemaligen DDR seit 1991) > 100 1995 Deutschland (einschließlich der ehemaligen DDR seit 1991) > 101 1996 Deutschland (einschließlich der ehemaligen DDR seit 1991) > 370 1999 Österreich > 372 2001 Österreich > 375 2004 Österreich > 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@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 ______________________________________________ R-help@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.
