I'm very new to SPSS (and stats in general) and therefore am having a problem. I have followed instructions from the SPSS help options/tutorials/etc to create multiple imputations for running binary logistic regression but I'm receiving a message which says:
Warnings Due to redundancies, degrees of freedom have been reduced for one or more variables for split file Imputation Number = Original data. Since there are no cases this split file Imputation Number = 1 will be skipped. Since there are no cases this split file Imputation Number = 2 will be skipped. Since there are no cases this split file Imputation Number = 3 will be skipped. Since there are no cases this split file Imputation Number = 4 will be skipped. Since there are no cases this split file Imputation Number = 5 will be skipped.
What reasons can there be for seeing this message? I do have cases, so I am very confused, but as I said, I know basically nothing about using SPSS so I'm probably making a mistake that I can't figure out.
Hi.
I'm very new to SPSS (and stats in general) and therefore am having a problem. I have followed instructions from the SPSS help options/tutorials/etc to create multiple imputations for running binary logistic regression but I'm receiving a message which says:
Warnings
Due to redundancies, degrees of freedom have been reduced for one or more variables for split file Imputation Number = Original data.
Since there are no cases this split file Imputation Number = 1 will be skipped.
Since there are no cases this split file Imputation Number = 2 will be skipped.
Since there are no cases this split file Imputation Number = 3 will be skipped.
Since there are no cases this split file Imputation Number = 4 will be skipped.
Since there are no cases this split file Imputation Number = 5 will be skipped.
What reasons can there be for seeing this message? I do have cases, so I am very confused, but as I said, I know basically nothing about using SPSS so I'm probably making a mistake that I can't figure out.
Any help/advice would be much appreciated.