Timberlake - Cytel

Back

Calibration of Crash Dummies in Automobile Safety Tests
Source: Hardle and Stoker, 1989
Cytel's LogXact 5 vs. SAS's PROC LOGISTIC:

Data from 58 simulated car crashes were analyzed. The relationship between the crash outcome (fatal, non-fatal) and 3 covariates was modeled.

ACL = acceleration
VEL = velocity
AGE = designed "age" of the crash dummy

The results are presented below. SAS fails to fit the logistic regression model -- only LogXact 5 can do it.

LOGXACT 5 RESULTS

=============================================================================================
Parameter Estimates
=============================================================================================
                   Point Estimate            Confidence interval and P-value for Beta
         Type  Beta        SE(Beta)    Type        95.0%     C.I.            Pvalue   SE      
                                                   Lower       Upper       2*1-sided   
=============================================================================================
acl       MLE  0.0175      0.0146      Asymptotic  -0.0112     0.0462      0.2319              
          CMLE 0.0129      0.0136      Monte Carlo -0.0128     0.0434      0.3402      0.0075    
                                       ( Seed=1038337854,Samples=10000 )

age       MLE  -0.1398     0.3285      Asymptotic  -0.7837     0.5040      0.6704              
          MUE  -0.1512     NA          Monte Carlo -INF        0.9986      0.8364      0.0099    
                                       ( Seed=1038337906,Samples=10000 )

vel       MLE  -0.0663     0.2521      Asymptotic  -0.5605     0.4279      0.7925              
          CMLE -0.5566     0.6415      Monte Carlo -2.6393     0.3476      0.5474      0.0089    
                                       ( Seed=1038337921,Samples=10000 )

age.vel   MLE  0.0068      0.0073      Asymptotic  -0.0075     0.0211      0.3485              
          CMLE 0.0067      0.0074      Monte Carlo -0.0071     0.0220      0.3578      0.0077    
                                       ( Seed=1038337935,Samples=10000 )

%CONST    MLE  -5.4304     11.2677     Asymptotic  -27.5148    16.6540     0.6298              
=============================================================================================

Analysis time: 00:01:34
=============================================================================================