li sex aop  n y
1  0   0   0  3 3
2  0   0   1  2 2
3  0   1   0  4 4
4  0   1   1  1 1
5  1   0   0  5 5
6  1   0   1  5 3
7  1   1   0  9 5
8  1   1   1 17 6

 Regular Logistic Regression for Sarcoma Data  

Call:  glm(formula = cbind(y, n - y) ~ li + sex + aop, family = "binomial", 
    data = goorin)

Coefficients:
(Intercept)           li          sex          aop  
     23.492      -21.384       -1.636       -1.220  

Degrees of Freedom: 7 Total (i.e. Null);  4 Residual
Null Deviance:	    19.43 
Residual Deviance: 1.628 	AIC: 17.67

 Exact Logistic Regression  
$coeffs
       li 
-1.793194 

$coeffs.ci
   lower     upper
li  -Inf 0.2123706

$p.values
   li 
0.043 

$p.values.se
        li 
0.01359667 

$mc
Markov Chain Monte Carlo (MCMC) output:
Start = 1 
End = 1000 
Thinning interval = 1 
        li

$mc.size
  li 
1000 

$obs.suff.stat
li 
19 

$distribution
$distribution$li
     li  freq
[1,] 19 0.043
[2,] 24 0.058
[3,] 23 0.103
[4,] 20 0.201
[5,] 21 0.291
[6,] 22 0.304


$call.history
$call.history[[1]]
elrm(formula = y/n ~ li + sex + aop, interest = ~li, dataset = goorin)


$dataset
  li sex aop  n y
1  0   0   0  3 3
2  0   0   1  2 2
3  0   1   0  4 4
4  0   1   1  1 1
5  1   0   0  5 5
6  1   0   1  5 3
7  1   1   0  9 5
8  1   1   1 17 6

$last
[1] 2 1 1 1 5 5 9 5

$r
[1] 4

$ci.level
[1] 95

attr(,"class")
[1] "elrm"
Conditional item response (column) probabilities,
 by outcome variable, for each class (row) 
 
$nsat
           Pr(1)  Pr(2)  Pr(3)
class 1:  0.1909 0.2502 0.5589
class 2:  0.6974 0.3026 0.0000

$ninf
           Pr(1)  Pr(2)  Pr(3)
class 1:  0.2652 0.4132 0.3217
class 2:  0.6383 0.3400 0.0216

$ncont
           Pr(1)  Pr(2)
class 1:  0.4484 0.5516
class 2:  0.3644 0.6356

$ntype
           Pr(1)  Pr(2)  Pr(3) Pr(4)
class 1:  0.2902 0.4511 0.1517 0.107
class 2:  0.1095 0.4649 0.1187 0.307

Estimated class population shares 
 0.711 0.289 
 
Predicted class memberships (by modal posterior prob.) 
 0.674 0.326 
 
========================================================= 
Fit for 2 latent classes: 
========================================================= 
number of observations: 1681 
number of estimated parameters: 17 
residual degrees of freedom: 54 
maximum log-likelihood: -6839.756 
 
AIC(2): 13713.51
BIC(2): 13805.77
G^2(2): 135.018 (Likelihood ratio/deviance statistic) 
X^2(2): 130.5442 (Chi-square goodness of fit)