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The MDS Procedure |

The OUTFIT= data set contains various measures of goodness and badness of fit. There is one observation for the entire sample plus one observation for each matrix. For the CONDITION=ROW option, there is also one observation for each row.

The OUTFIT= data set contains the following variables:

- BY variables, if any
- _ITER_ (if the OUTITER option is specified), a numeric variable containing the iteration number
- _DIMENS_, a numeric variable containing the number of dimensions
- _MATRIX_ or the variable in the MATRIX statement, identifying the data matrix or subject to which the observation pertains
- _LABEL_ or the variable in the ID statement, containing the variable label or value of the ID variable of the object to which the observation pertains when CONDITION=ROW
- _NAME_, a character variable of length 8 containing the variable name of the object or dimension to which the observation pertains when CONDITION=ROW
- N, the number of nonmissing data
- WEIGHT, the weight of the partition
- CRITER, the badness-of-fit criterion
- DISCORR, the correlation between the transformed data and the distances for LEVEL=ORDINAL or the correlation between the data and the transformed distances otherwise
- UDISCORR, the correlation uncorrected for the mean between the transformed data and the distances for LEVEL=ORDINAL or the correlation between the data and the transformed distances otherwise
- FITCORR, the correlation between the fit-transformed data and the fit-transformed distances
- UFITCORR, the correlation uncorrected for the mean between the fit-transformed data and the fit-transformed distances

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