[R] question regarding logit regression using glm

[Haibo Huang]

I got the following warning messages when I did a
binomial logit regression using glm():

Warning messages: 
1: Algorithm did not converge in: glm.fit(x = X, y =
Y, weights = weights, start = start, etastart =
etastart,  
2: fitted probabilities numerically 0 or 1 occurred
in: glm.fit(x = X, y = Y, weights = weights, start =
start, etastart = etastart,  

Can some one share your thoughts on how to solve this
problem? Please read the following for details. Thank
you very much!

Best,
Ed


> Lease=read.csv("lease.csv", header=TRUE)
> Lease$ET = factor(Lease$EarlyTermination)
> SICCode=factor(Lease$SIC.Code)
> TO=factor(Lease$TenantHasOption)
> LO=factor(Lease$LandlordHasOption)
> TEO=factor(Lease$TenantExercisedOption)
> 
> RegA=glm(ET~1+MSA, 
+ family=binomial(link=logit), data=Lease,
weights=Origil.SQFT)
Warning messages: 
1: Algorithm did not converge in: glm.fit(x = X, y =
Y, weights = weights, start = start, etastart =
etastart,  
2: fitted probabilities numerically 0 or 1 occurred
in: glm.fit(x = X, y = Y, weights = weights, start =
start, etastart = etastart,  
> summary(RegA)

Call:
glm(formula = ET ~ 1 + MSA, family = binomial(link =
logit), 
    data = Lease, weights = Origil.SQFT)

Deviance Residuals: 
       Min          1Q      Median          3Q        
Max  
-6.038e+03  -2.066e-06   0.000e+00   0.000e+00  
6.720e+03  

Coefficients:
                      Estimate Std. Error    z value
Pr(>|z|)    
(Intercept)          5.711e+00  8.466e-02  6.745e+01  
<2e-16 ***
MSAAnchorage        -6.493e+00  8.541e-02 -7.602e+01  
<2e-16 ***
MSAAtlanta           6.894e+14  2.310e+04  2.985e+10  
<2e-16 ***
MSAAustin           -9.362e+14  4.954e+04 -1.890e+10  
<2e-16 ***
MSABoston           -2.474e+15  2.151e+04 -1.150e+11  
<2e-16 ***
MSACharlotte        -2.150e+15  7.265e+04 -2.960e+10  
<2e-16 ***
MSAChicago          -1.174e+15  2.057e+04 -5.707e+10  
<2e-16 ***
MSACleveland        -7.607e+14  7.046e+04 -1.080e+10  
<2e-16 ***
MSAColumbus         -2.768e+15  1.685e+05 -1.642e+10  
<2e-16 ***
MSADallas            2.061e+14  3.261e+04  6.321e+09  
<2e-16 ***
MSADenver            5.470e+14  3.366e+04  1.625e+10  
<2e-16 ***
MSAEast Bay         -6.191e+01  1.344e+05  -4.61e-04  
     1    
MSAFt. Worth        -6.565e+00  8.483e-02 -7.739e+01  
<2e-16 ***
MSAHouston          -2.735e+15  3.576e+04 -7.648e+10  
<2e-16 ***
MSAIndianapolis     -7.483e+14  6.588e+04 -1.136e+10  
<2e-16 ***
MSALos Angeles      -1.388e+15  2.887e+04 -4.809e+10  
<2e-16 ***
MSAMinneapolis      -1.011e+15  2.731e+04 -3.702e+10  
<2e-16 ***
MSANashville         2.143e+01  9.395e+04   2.28e-04  
     1    
MSANew Orleans      -3.370e+15  5.038e+04 -6.689e+10  
<2e-16 ***
MSANew York         -2.526e+15  2.969e+04 -8.507e+10  
<2e-16 ***
MSANorfolk          -5.614e+01  2.020e+06  -2.78e-05  
     1    
MSAOakland-East Bay -2.272e+15  3.642e+04 -6.239e+10  
<2e-16 ***
MSAOrange County    -5.165e+14  2.428e+04 -2.128e+10  
<2e-16 ***
MSAOrlando          -3.215e+15  1.096e+05 -2.933e+10  
<2e-16 ***
MSAPhiladelphia     -8.871e+14  4.948e+04 -1.793e+10  
<2e-16 ***
MSAPhoenix          -1.156e+01  8.807e-02 -1.313e+02  
<2e-16 ***
MSAPortland          7.604e+14  3.841e+04  1.980e+10  
<2e-16 ***
MSARaleigh-Durham   -4.312e+01  1.294e+05  -3.33e-04  
     1    
MSARiverside         1.626e+15  4.645e+05  3.500e+09  
<2e-16 ***
MSASacramento       -9.873e+14  5.345e+04 -1.847e+10  
<2e-16 ***
MSASalt Lake City    1.793e+15  2.029e+05  8.839e+09  
<2e-16 ***
MSASan Antonio       9.451e+14  9.473e+04  9.977e+09  
<2e-16 ***
MSASan Diego        -3.740e+15  6.651e+04 -5.623e+10  
<2e-16 ***
MSASan Francisco     3.109e+14  2.394e+04  1.299e+10  
<2e-16 ***
MSASan Jose          7.392e+14  2.961e+04  2.497e+10  
<2e-16 ***
MSASeattle          -2.250e+15  1.581e+04 -1.423e+11  
<2e-16 ***
MSASt. Louis        -2.606e+15  1.801e+05 -1.447e+10  
<2e-16 ***
MSAStamford         -6.592e+00  8.469e-02 -7.784e+01  
<2e-16 ***
MSAWashington DC     8.460e+13  3.319e+04  2.549e+09  
<2e-16 ***
MSAWest Palm Beach  -3.924e+01  2.308e+05  -1.70e-04  
     1    
---
Signif. codes:  0 `***' 0.001 `**' 0.01 `*' 0.05 `.'
0.1 ` ' 1 

(Dispersion parameter for binomial family taken to be
1)

    Null deviance:  123111026  on 9302  degrees of
freedom
Residual deviance: 3028559052  on 9263  degrees of
freedom
AIC: 3028559132

Number of Fisher Scoring iterations: 25

> anova(RegA)
Analysis of Deviance Table

Model: binomial, link: logit

Response: ET

Terms added sequentially (first to last)


       Df   Deviance Resid. Df Resid. Dev
NULL                      9302  123111026
MSA    39          0      9263 3028559052
>