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[Calculating Pearson residual in logistic regressions: a comparison between SPSS and SAS]
Objective:
To compare the results of Pearson residual calculations in logistic regression models using SPSS and SAS.
Methods:
We reviewed Pearson residual calculation methods, and used two sets of data to test logistic models constructed by SPSS and STATA. One model contained a small number of covariates compared to the number of observed. The other contained a similar number of covariates as the number of observed.
Results:
The two software packages produced similar Pearson residual estimates when the models contained a similar number of covariates as the number of observed, but the results differed when the number of observed was much greater than the number of covariates.
Conclusion:
The two software packages produce different results of Pearson residuals, especially when the models contain a small number of covariates. Further studies are warranted.
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