Qualitative predictor variables not appearing in regression summary output R -


i have big dataset use run linear regression models qualitative predictor variables. call dataset wn , qualitative variables ostate , dstate (states in us). here see there 62 unique values of ostate , dstate within wn:

> unique(wn$ostate) [1] ny ma pa de dc va md wv nc ri sc nh ga fl al tn ms me ky oh in mi vt ia wi mn sd nd mt ct il mo ks ne nj la ar ok tx co wy id ut az nm nv ca or wa 62 levels: aa ae ak al ap ar az ca co ct dc de fl fm ga gu hi ia id il in ks ky la ma md me mh mi mn mo mp ms mt nc nd ne nh nj nm nv ny oh ok or pa pr pw ri sc sd tn tx ut va vi vt wa ... wy > unique(wn$dstate) [1] ma ri nh me vt ct ny nj pa de dc va md wv nc sc ga fl al tn ms ky oh in mi ia wi mn sd nd mt il mo ks ne la ar ok tx co wy id ut az nm nv ca or wa 62 levels: aa ae ak al ap ar az ca co ct dc de fl fm ga gu hi ia id il in ks ky la ma md me mh mi mn mo mp ms mt nc nd ne nh nj nm nv ny oh ok or pa pr pw ri sc sd tn tx ut va vi vt wa ... wy

now running regression model predict rate distance, ostate , dstate follows:

> wn.lr = lm(wn$rate~wn$distance+wn$ostate+wn$dstate)

when check regression summary, see 48 ostate , dstate predictors populated, , remaining 14 missing. small part of summary output given below. example see ostateal missing in output: 

> summary(wn.lr)  call: lm(formula = wn$rate ~ wn$distance + wn$ostate + wn$dstate)  residuals:     min      1q  median      3q     max  -2370.3  -218.4   -18.9   170.8  9105.7   coefficients:               estimate std. error t value pr(>|t|)     (intercept)  1.208e+03  6.632e+00 182.171  < 2e-16 *** wn$distance  1.626e+00  3.111e-03 522.722  < 2e-16 *** wn$ostatear  2.000e+02  7.294e+00  27.419  < 2e-16 *** wn$ostateaz  1.981e+02  8.372e+00  23.667  < 2e-16 *** wn$ostateca  1.056e+02  7.919e+00  13.340  < 2e-16 *** wn$ostateco  1.323e+02  7.332e+00  18.043  < 2e-16 *** wn$ostatect -2.019e+02  1.827e+01 -11.048  < 2e-16 *** wn$ostatedc  5.711e+02  2.178e+01  26.223  < 2e-16 ***

on other hand, when check entities ostate = "al", see there on 6000 rows:

> wnnew<-subset(wn,ostate=="al") > nrow(wnnew) [1] 6213

any explanation this?

this because of aliasing (i.e. model overidentified). example, massachusetts level in both dstate , ostate variables, think effect in both treatments can't separated.


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