Monte Carlo Results Spreadsheet

The Monte Carlo Results Spreadsheet can be created from the Quick tab of the Monte Carlo Results dialog box. It contains an extensive summary of the outcome of the Monte Carlo experiment. The spreadsheet stores the results with the replications in rows, and the data for each replication in columns. Which data are stored depends on the options selected in the Monte Carlo Analysis dialog box.

As a Monte Carlo experiment is performed, information about the analysis results for each Monte Carlo replication is stored in memory, and is displayed in an overall results spreadsheet at the end of the experiment. Results for each replication are stored in a new row of the spreadsheet. The basic results, stored for all Monte Carlo experiments, include the Monte Carlo seeds used for each replication, the discrepancy function value, the number of iterations required, and a variety of indicators used to determine whether iteration converged satisfactorily.

Following are the codes for the variable names:

SEED1
This is the first of the two Monte Carlo seeds.
SEED2
This is the second seed, used only in Contaminated Normal distribution generation.
TERMCODE
This is the termination code for the analysis. If this is zero, the analysis apparently converged normally. If not, then the following codes apply.
  1. The relative function change criterion was below the criterion value.  This can occur when the function has stabilized, but the gradient and relative cosine criteria do not go to zero, because one of the parameters is on a boundary value.
  2. The line search algorithm was unable to reduce the discrepancy function along the searched direction.
  3. The number of iterations reached the maximum permissible value. If necessary, this value may be altered in the Analysis Parameters dialog box.
  4. Singular covariance matrix was encountered during iteration. On occasion, the parameters will be changed to values that yield a singular estimated covariance matrix. When this happens in maximum likelihood estimation, the discrepancy function cannot be evaluated, so iteration is stopped.
  5. (this value is currently not in use)
  6. The iteration was terminated by user request, i.e., the user stopped iteration with the ESC key or the Cancel button.
DISCREP
The value of the discrepancy function after iteration.
RCOS
The maximum residual cosine criterion.
GRADIENT
The maximum absolute value of the gradient elements after iteration.
NUM_ITER
The number of iterations required before termination.
ICSC
The ICSF invariance criterion.
ICS
The ICS invariance criterion.
RED_PAR
The number of redundant parameters.
RED_CON
The number of redundant constraints.
BOUNDARY
The number of active inequality constraints (NAIC), or "boundary cases," after iteration.
CHI_SQR
The Chi-square goodness-of-fit statistic.
DF
The number of degrees of freedom for the Chi-square statistic.
PLEVEL
The probability level for the Chi-square statistic.
PAR_#
The parameter values, numbered as they are in the PATH1 analysis syntax. So, for example, PAR_23 is the value for the free parameter numbered 23 in the analysis syntax.

SE_#.  The standard errors, numbered in the same way as the parameter numbers.

RMS_LO
The lower endpoint of the 90% confidence interval for the Steiger-Lind (1980) RMS index.
RMS_PT
The point estimate for the Steiger-Lind (1980) RMS index.
RMS_HI
The upper endpoint of the 90% confidence interval for the Steiger-Lind (1980) RMS index.
NCP_LO
The lower endpoint of the 90% confidence interval for the population discrepancy function.
NCP_PT
The point estimate for the population discrepancy function.
NCP_HI
The upper endpoint of the 90% confidence interval for the population discrepancy function.
AIC
The rescaled Akaike information criterion.
BIC
The Schwarz Bayesian criterion.
BR_CUD
The Browne-Cudeck single sample cross-validation index.
GAMMA_LO
The upper endpoint of the 90% confidence interval for the population gamma index.
GAMMA_PT
The point estimate for the population gamma index.
GAMMA_HI
The upper endpoint of the 90% confidence interval for the population gamma index.
GAMAD_LO
The upper endpoint of the 90% confidence interval for the adjusted population gamma index.
GAMAD_PT
The point estimate for the adjusted population gamma index.
GAMAD_HI
The upper endpoint of the 90% confidence interval for the adjusted population gamma index.  
IRGLS
The IRGLS discrepancy function, if maximum likelihood estimates were obtained.