R help - Feb 2010 - Ordered Logit in R

I'm trying to run an ordered logistic regression model. I've run the
following code, but the output does not provide the p-values. Is there some
command to include the p-values in the output.




reg2 <- polr(trade1 ~ age2 + education2 + personal2 + economy2 + partisan2 +
employment2 + union2 + home2 + market2 + race2 + income2)

summary(reg2)

Re-fitting to get Hessian#
Call:
polr(formula = trade1 ~ age2 + education2 + personal2 + economy2 + 
    partisan2 + employment2 + union2 + home2 + market2 + race2 + 
    income2)

Coefficients:
                   Value  Std. Error    t value
age2         0.003499077 0.006006362  0.5825617
education2  -0.232741995 0.048080310 -4.8406924
personal2   -0.117131182 0.089053504 -1.3152900
economy2    -0.308168069 0.104511809 -2.9486435
partisan2   -0.103307636 0.091802806 -1.1253211
employment2 -0.097811420 0.378070202 -0.2587123
union2       0.038079199 0.168729702  0.2256817
home2        0.274581851 0.157926099  1.7386730
market2     -0.195350757 0.153563376 -1.2721181
race2       -0.057407307 0.112952281 -0.5082439
income2     -0.130017473 0.068047763 -1.9106796

Intercepts:
                                             Value   Std. Error t value
5. Oppose|0. Haven't thought much about this -3.0450  0.8797    -3.4613
0. Haven't thought much about this|1. Favor  -1.1990  0.8732    -1.3730

Residual Deviance: 1609.821 
AIC: 1635.821 
(936 observations deleted due to missingness)


Help!!!!!!!!!!!!

I ran the follow code for an ordered logit, but don't know why two levels of
my dependent variable are at the topic of my list of variables.

I don't know why this appears, and what I'm supposed to take from them

y>=0. Haven't thought much about this  
y>=1. Favor  


library(Design)
two <- lrm(trade1 ~ age2 + education2 + personal2 + economy2 + partisan2 +
employment2 + union2 + home2 + market2 + race2 + income2)
two
summary(two)


#Logistic Regression Model
#
#lrm(formula = trade1 ~ age2 + education2 + personal2 + economy2 + 
#    partisan2 + employment2 + union2 + home2 + market2 + race2 + 
#    income2)
#
#Frequencies of Responses
#                         5. Oppose 0. Haven't thought much about this 
#                               258                                311 
#                          1. Favor 
#                               209 
#
#Frequencies of Missing Values Due to Each Variable
#     trade1        age2  education2   personal2    economy2   partisan2 
#        210           0           3           7          16         134 
#employment2      union2       home2     market2       race2     income2 
#        678           5          59         207          10          82 
#
#       Obs  Max Deriv Model L.R.       d.f.          P          C        Dxy 
#       778      1e-10      79.47         11          0      0.647      0.295 
#     Gamma      Tau-a         R2      Brier 
#     0.296      0.194       0.11      0.191 
#
#                                      Coef      S.E.     Wald Z P     
#y>=0. Haven't thought much about this  3.045016 0.879724  3.46  0.0005
#y>=1. Favor                            1.198983 0.873244  1.37  0.1697
#age2                                   0.003499 0.006006  0.58  0.5602
#education2                            -0.232741 0.048080 -4.84  0.0000
#personal2                             -0.117132 0.089053 -1.32  0.1884
#economy2                              -0.308168 0.104512 -2.95  0.0032
#partisan2                             -0.103308 0.091803 -1.13  0.2605
#employment2                           -0.097818 0.378070 -0.26  0.7958
#union2                                 0.038079 0.168730  0.23  0.8215
#home2                                  0.274581 0.157926  1.74  0.0821
#market2                               -0.195350 0.153563 -1.27  0.2033
#race2                                 -0.057408 0.112952 -0.51  0.6113
#income2                               -0.130017 0.068048 -1.91  0.0560