Four techniques to dealwith missing data in educational and psychological research

Yahya H. Nassar, Thaer A. Ghbari, Jalal K. Damra

Research output: Contribution to journalArticlepeer-review


This study aimed at presenting the problems of using four techniques of dealing with missing data in psychological and educational research such as: listwise deletion, pairwise deletion, mean imputation, and regression imputation. Each technique is discussed in terms of its procedures or its related problems. The research also consisted of hypothetical data by which the procedure was conducted and analyzed to test the effects of each on the descriptive statistics (means and standard deviations), correlation coefficients, and the weights of predicting variables in the regression analysis. The results showed that the researchers in psychology and education should have the awareness of these techniques and their problems, and it is preferred to test the best of them to deal with the missing data, instead of using the popular embedded techniques in some statistical program such as SPSS or SAS which deal with the missing data spontaneously.

Original languageEnglish
Pages (from-to)100-115
Number of pages16
JournalJournal of Institutional Research South East Asia
Issue number2
Publication statusPublished - 2014
Externally publishedYes


  • Correlation coefficients
  • Listwise deletion
  • Mean imputation
  • Missing data
  • Pairwise deletion
  • Problems
  • Regression imputation
  • Statistical packages
  • Weights of predictors

ASJC Scopus subject areas

  • Education


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