﻿ CONVERGE= select convergence criteria

# CONVERGE= select convergence criteria = Either

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This selects which of LCONV= and RCONV= set the convergence criterion. See convergence considerations.

 CONVERGE=L LCONV= for "Logit change size" controls convergence. Iteration stops when the biggest logit change is less or equal to LCONV=, or when the biggest logit change size increases (divergence). CONVERGE=R RCONV= for "Residual size" controls convergence. Iteration stops when the biggest residual score is less or equal to RCONV=, or when the biggest residual size increases (divergence). CONVERGE=E Either LCONV= for "Logit change size" or RCONV= for "Residual size" controls convergence. Iteration stops when the biggest logit change is less or equal to LCONV=, or when the biggest residual score is less or equal to RCONV=, or when both the biggest logit change size increases and the biggest residual size increases (divergence). CONVERGE=B Both LCONV= for "Logit change size" and RCONV= for "Residual size" controls convergence. Iteration stops when both the biggest logit change is less or equal to LCONV= and the biggest residual score is less or equal to RCONV=, or when both the biggest logit change size increases and the biggest residual size increases (divergence). CONVERGE=F Force both LCONV= for "Logit change size" and RCONV= for "Residual size" to control convergence. Iteration stops when both the biggest logit change is less or equal to LCONV= and the biggest residual score is less or equal to RCONV=.

Example 1: We want to be take a conservative position about convergence, requiring both small logit changes and small residual sizes when iteration ceases.

CONVERGE=Both

Example 2: We need very high precision, then specify:

CONVERGE=BOTH ; both score-residual and logit-change criteria

RCONV=.001 ; at most, one tenth of the smallest score residual needed.

LCONV=.00001  ; at most, one tenth of the highest precision to be reported.

These values are much, much smaller than the natural precision of the data, which is .5 raw score points, or the logit precision (S.E.) of the ability measures.

Example 3: We want to set the convergence criteria to match BIGSTEPS version 2.59

CONVERGE=B ; the criteria were LCONV= and RCONV=

RCONV= 0.5 ; the BIGSTEPS standards or whatever value you used

LCONV= .01

Example 4: We want to set the convergence criteria to match Winsteps version 3.20

CONVERGE=E ; the criterion was LCONV or RCONV

RCONV= 0.5 ; the 3.20 standards or whatever value you used

LCONV= .01

Example 5: We want the convergence criteria to match Winsteps version 2.85

CONVERGE= F ; force both LCONV and RCONV to be met

RCONV= 0.5 ; the 2.85 standards or whatever value you used

LCONV= .01

You may also want:

WHEXACT=NO ; centralized Wilson-Hilferty was the default

Example 6: Question: With anchored analyses, iterations never stop!

|----------------------------------------------------------------------------|

|    JMLE     MAX SCORE   MAX LOGIT    LEAST CONVERGED     CATEGORY    STEP  |

| ITERATION   RESIDUAL*    CHANGE    EXID   BYCASE   CAT   RESIDUAL   CHANGE |

|----------------------------------------------------------------------------|

|       1      -239.04       .5562    1993    392*      6      85.70   -.5960|

|       2      -105.65      -.1513    1993    392*      4     -28.92    .2745|

.....

|      18        -5.35      -.0027    2228    352*      3       2.35    .0146|

|      19        -5.16       .0029    2228    352*      3       2.31    .0106|

|      20        -5.05       .0025    2228    352*      3       2.28    .0055|

|      21        -5.00       .0010    2228    352*      3       2.26    .0075|

|      22        -4.99      -.0008    2228    352*      3       2.25    .0025|

.....

|     170        -5.00      -.0011    1377    352*      3       1.96    .0109|

|     171        -5.00       .0018     187    352*      3       1.96    .0019|

.....

The standard convergence criteria in Winsteps are preset for "free" analyses. With anchored analyses, convergence is effectively reached when the logit estimates stop changing in a substantively meaningful way. This has effectively happened by iteration 20. Note that the logit changes are less than .01 logits - i.e., even the biggest change would make no difference to the printed output (which is usually reported to 2 decimal places)

To have the current Winsteps do this automatically, set

CONVERGE=L

LCONV=.005   ; set to stop at iteration 22 - to be on the safe side.

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