The purpose of this study is to examine the reliability coefficient estimates under the conditions of sample size, number of categories and missing data rates according to the methods of missing data imputation. Within this context, the data sets were generated 20 number of items for sample size 500 and 5000 respectively. The full data sets were deleted under missing completely at random condition by five, ten, twenty and thirty percent. After deleting data sets, missing data techniques 0, mean, regression and multiple imputation were carried out on incomplete data sets. Reliability coefficients which used this study were Cronbach a, standardized alpha, Armor's theta, Guttman lambda 4, Guttman lambda 5, Guttman lambda 6 and McDonald's omega, and the reliability estimations were compared with the full data sets of the reliability estimations. Results show that there was not a single coefficient which was more reliable based on missing data imputation methods. It is suggested that the researcher should use multiple assignment and regression assignment methods, but not the zero imputation method, as missing data imputation methods in the analysis of the reliability coefficients discussed in the research.