# Missing Level on linear model tests

##### New Member
So I'm an R newbie, we're attempting to use it for some regression analysis at work on some of our data sets. To start we wanted to take a very simple data set that we had and attempt to fit a linear model to it.

The problem that I'm running into is that once I import the data file and perform the lm() function I lose one of my levels, I don't understand where it has gone or if I'm just interpreting the output wrong.

the output looks like this:

Code:
 fit<-lm(TotalPercPaid120~AgeBucket)
> summary(fit)

Call:
lm(formula = TotalPercPaid120 ~ AgeBucket)

Residuals:
Min      1Q  Median      3Q     Max
-90.496  -0.495   0.264   0.317  45.452

Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept)       0.597990   0.009114  65.611  < 2e-16 ***
AgeBucket25      -0.087959   0.015536  -5.662 1.51e-08 ***
AgeBucket30      -0.104718   0.016645  -6.291 3.17e-10 ***
AgeBucket35      -0.102780   0.016092  -6.387 1.70e-10 ***
AgeBucket40      -0.072274   0.015402  -4.693 2.70e-06 ***
AgeBucket45      -0.039197   0.014904  -2.630  0.00854 **
AgeBucket50       0.033393   0.013828   2.415  0.01574 *
AgeBucket55       0.085377   0.012923   6.607 3.96e-11 ***
AgeBucket60       0.116011   0.012731   9.113  < 2e-16 ***
AgeBucket65       0.162438   0.012688  12.802  < 2e-16 ***
AgeBucket70       0.109460   0.013485   8.117 4.85e-16 ***
AgeBucket75       0.086453   0.014602   5.921 3.22e-09 ***
AgeBucket80       0.121772   0.015791   7.711 1.26e-14 ***
AgeBucket85       0.137719   0.017063   8.071 7.08e-16 ***
AgeBucket90       0.154927   0.021803   7.106 1.21e-12 ***
AgeBucket95       0.163869   0.038299   4.279 1.88e-05 ***
AgeBucketPlus100  0.052145   0.068789   0.758  0.44843
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1

Residual standard error: 0.728 on 64449 degrees of freedom
Multiple R-squared: 0.01448,    Adjusted R-squared: 0.01423
F-statistic: 59.18 on 16 and 64449 DF,  p-value: < 2.2e-16
there should be another level "AgeBucket16", it's the first level of the AgeBucket factor.

I get the same problem when I perform an anova using the same factors, I lose the first level of both my "AgeBucket" factor and my "Hospital" factor.

Code:
 fit2<-aov(TotalPercPaid120~AgeBucket+Hospital)
> summary(fit2)
Df Sum Sq Mean Sq F value Pr(>F)
AgeBucket      16    502   31.36   59.24 <2e-16 ***
Hospital        1     39   38.72   73.15 <2e-16 ***
Residuals   64448  34118    0.53
---
Signif. codes:  0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
> coef(fit2)
(Intercept)      AgeBucket25      AgeBucket30      AgeBucket35      AgeBucket40      AgeBucket45      AgeBucket50      AgeBucket55      AgeBucket60      AgeBucket65
0.63715260      -0.10455534      -0.11868351      -0.11665114      -0.08450580      -0.05072533       0.02153494       0.07419295       0.10470710       0.15132806
AgeBucket70      AgeBucket75      AgeBucket80      AgeBucket85      AgeBucket90      AgeBucket95 AgeBucketPlus100  HospitalSt Mary
0.09947468       0.07662257       0.11098498       0.12526939       0.14027786       0.15178454       0.03671460      -0.05010209
can anyone shed some light on what I'm not picking up on??