Kim J and Curry J: The treatment of missing data in multivariate analysis, Sosiological Methods & Research, 6 (1977) 215-240. Home/Search Document Not in Database Summary Related Articles Check |
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Studies on the Experimental Construction of a Neural.. - Pesonen (1998) (Correct)
....value for the missing data values [BF95] Often this is not possible in practice, because it would be too laborious, and thus some automated systems must be used. The third basic solution is to replace the missing data values with new values which are generated in an appropriate way [BL75, DLR77, KC77, CBH 91, Lam94] When a data value has not been recorded, one reason for this can be that there has been no reason to record a normal value. If this is true, then a good choice would be to replace the missing data values with the corresponding value that a healthy patient would normally ....
Kim J and Curry J: The treatment of missing data in multivariate analysis, Sosiological Methods & Research, 6 (1977) 215-240.
Software Cost Estimation with Incomplete Data - Strike, Emam, Madhavji (2000) (1 citation) (Correct)
....they are the variables collected through a questionnaire. While one should strive to minimise missing values, in practice their existence is usually unavoidable. Missing values are not unique to software cost estimation, but is a problem that concerns empirical scientists in other disciplines [48][38] 55] V21 2 The most common factors that lead to missing data include individuals not responding to all questions in a questionnaire, either because they run out of time, they do not understand the questions or they do not have sufficient knowledge to answer the questions and opt not to ....
....that have missing values (this is called listwise deletion) In fact, this is the default approach in most statistical packages [56] This, however, can result in discarding large proportions of a data set and hence in a loss of information that was costly to collect. For example, Kim and Curry [48] note that with only 2 of the values missing at random in each of 10 variables, one would lose 18.3 of the observations on average using listwise deletion. Furthermore, with 5 variables having 10 of their values missing at random, 41 of the observation would be lost with listwise deletion, on ....
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J. Kim and J. Curry: "The Treatment of Missing Data in Multivariate Analysis". In Social Methods & Research. 6:215-240, 1977.
Large-Scale Imputation For Complex Surveys - Marker, Judkins, Winglee (1999) (Correct)
....1989; Little 1988a) However, it is a computer intensive procedure, and software for its use with a particular form of analysis may not be readily available. 35 As compared with the CC approach, the AC approach has the attraction of making fuller use of the available data. In a simulation study, Kim and Curry (1977) found the AC approach to be superior to the CC approach with weakly correlated data. A limitation to the AC approach is that it may produce a covariance matrix that is not positive definite, an outcome that poses problems for model estimation (yielding indeterminate slopes in a regression ....
Kim, J.O. and Curry, J. (1977). Treatment of Missing Data in Multivariate Analysis. Sociological Methods and Research, 6, 215-240.
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