000 02276cam a2200337 a 4500
003 EG-GiCUC
005 20250223031448.0
008 160329s2015 ua f m 000 0 eng d
040 _aEG-GiCUC
_beng
_cEG-GiCUC
041 0 _aeng
049 _aDeposite
097 _aPh.D
099 _aCai01.18.03.Ph.D.2015.Ab.T
100 0 _aAbdeltawab Ahmed Abdelaziz
245 1 0 _aTreating Missing Data /
_cAbdeltawab Ahmed Abdelaziz ; Supervised Mahmoud Riad Mahmoud , Samir Kamel Ashour
246 1 5 _aمعالجة القيم المفقودة
260 _aCairo :
_bAbdeltawab Ahmed Abdelaziz ,
_c2015
300 _a97 Leaves ;
_c30cm
502 _aThesis (Ph.D.) - Cairo University - Institute of Statistical Studies and Research - Department of Mathematical Statistics
520 _aMissing data is a very common problem in most empirical research areas. Missing data is present if the researcher fails to get the information from the sample. The problem of missing data in survey sampling is called the problem of non-response. It causes possible bias in estimators of population characteristics if no treatment is made to compensate for the non-response. These biases occur when the non-respondents are different from the respondents with respect to the study variable. Also, these biases are difficult to eliminate since the precise reasons for non- response are usually undetermined. Moreover, the efficiency of parameter estimation will be reduced and the results can be misleading which violated the statistical inference about population parameters. Imputation is commonly used to treat item non-response. Imputation aimed to replace the missing values with a plausible value to get a complete data set valid for inference. Mean method of imputation, ratio method of imputation, product method of imputation and regression method of imputation are most commonly used methods of imputation
530 _aIssued also as CD
653 4 _aImputation
653 4 _aMissing data
653 4 _aSimple random sample
700 0 _aMahmoud Riad Mahmoud ,
_eSupervisor
700 0 _aSamir Kamel Ashour ,
_eSupervisor
856 _uhttp://172.23.153.220/th.pdf
905 _aNazla
_eRevisor
905 _aSoheir
_eCataloger
942 _2ddc
_cTH
999 _c55771
_d55771