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| Titel: |
Imputation procedures for categorical data: their effects on the goodness-of-fit chi-square statistic |
| Auteur: |
Gimotty, Phyllis A. Brown, Morton B. |
| Verschenen in: |
Communications in statistics |
| Paginering: | Jaargang 19 (1990) nr. 2 pagina's 681-703 |
| Jaar: |
1990 |
| Inhoud: |
An imputation procedure is a procedure by which each missing value in a data set is replaced (imputed) by an observed value using a predetermined resampling procedure. The distribution of a statistic computed from a data set consisting of observed and imputed values, called a completed data set, is affecwd by the imputation procedure used. In a Monte Carlo experiment, three imputation procedures are compared with respect to the empirical behavior of the goodness-of- fit chi-square statistic computed from a completed data set. The results show that each imputation procedure affects the distribution of the goodness-of-fit chi-square statistic in 3. different manner. However, when the empirical behavior of the goodness-of-fit chi-square statistic is compared u, its appropriate asymptotic distribution, there are no substantial differences between these imputation procedures. |
| Uitgever: |
Taylor & Francis |
| Bronbestand: |
Elektronische Wetenschappelijke Tijdschriften |
Details van artikel 12 van 23 gevonden artikelen
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