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  • 标题:Using Residual Estimators to Detect Outliers and Potential Controlling Observations in Structural Equation Modelling: QQ Plot Approach
  • 本地全文:下载
  • 作者:A. R. Abdul-Aziz ; Albert Luguterah ; Bashiru I. I. Saeed
  • 期刊名称:Open Journal of Statistics
  • 印刷版ISSN:2161-718X
  • 电子版ISSN:2161-7198
  • 出版年度:2020
  • 卷号:10
  • 期号:5
  • 页码:905-914
  • DOI:10.4236/ojs.2020.105053
  • 出版社:Scientific Research Publishing
  • 摘要:The structural equation model (SEM) concept is generally influenced by the presence of outliers and controlling variables. To a very large extent, this could have consequential effects on the parameters and the model fitness. Though previous researches have studied outliers and controlling observations from various perspectives including the use of box plots, normal probability plots, among others, the use of uniform horizontal QQ plot is yet to be explored. This study is, therefore, aimed at applying uniform QQ plots to identifying outliers and possible controlling observations in SEM. The results showed that all the three methods of estimators manifest the ability to identify outliers and possible controlling observations in SEM. It was noted that the Anderson-Rubin estimator of QQ plot showed a more efficient or visual display of spotting outliers and possible controlling observations as compared to the other methods of estimators. Therefore, this paper provides an efficient way identifying outliers as it fragments the data set.
  • 关键词:Outliers;Controlling Observations;Estimators;QQ Plots;Structural Equation Modelling
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