scholarly journals MissMech: AnRPackage for Testing Homoscedasticity, Multivariate Normality, and Missing Completely at Random (MCAR)

2014 ◽  
Vol 56 (6) ◽  
Author(s):  
Mortaza Jamshidian ◽  
Siavash Jalal ◽  
Camden Jansen
2013 ◽  
pp. 1-7
Author(s):  
C. SIORDIA

Background:Item allocation (the assignment of plausible values to missing or illogical responses insurvey studies) is at times necessary in the production of complete data sets. In the American Community Survey(ACS), missing responses to health insurance coverage questions are allocated. Objectives:Because allocationrates may vary as a function of compositional characteristics, this project investigates how seven different healthinsurance coverage items vary in their degree of allocation along basic demographic variables. Methods: Datafrom the ACS 2010 1-year Public Use Microdata Sample file are used in a logistic regression model and tocalculate allocations rates. Results:The findings reveal that: males; people aged 65 and older; those who speakEnglish “very well” or “well”; US citizens; those out-of-poverty; and all racial/ethnic minority groups havehigher odds of experiencing a health insurance item allocation relative to their counterparts. Conclusions: Sincehealth insurance coverage allocations vary by demographic characteristics, further research is needed toinvestigate their mechanisms of missingness and how these may have implications for frailty related research.


2021 ◽  
Vol 6 (5) ◽  
pp. 43-49
Author(s):  
J. M. Aniesedo ◽  
C. N. Okoli

This study used the multivariate analysis of variance (MANOVA) test statistic to examine the impact of three categories feed used in the production of pig in Delta State. The multivariate test statistic considered are the Pillai – Bartlett trace, Wilks’ Test Statistic, Roy’s Largest Root Test Statistic, and the Lawley- Hotelling (LH) Statistic. The objectives include to: evaluate the robustness of the four Multivariate Analysis of Variance test statistics to ensure that the best is employed in multivariate analysis to guarantee most useful result in pig production; determine the relatively efficient test statistic for pig production; and determine the test statistic that is consistent across the sample sizes. Secondary source of data collection was used to obtain the data required for the analysis. The outcome of the study showed that the obtained data was multivariate normally distributed based on the result of the asymmetry-based multivariate normality test and the multivariate normality test based on the kurtosis test which makes the data suitable parametric multivariate method such as multivariate analysis of variance (MANOVA). The results show that the Wilks and Roy tests found a significant difference for the intercept. While the Pillai and LH tests could not find any significance. The Roy test was also found to be significant for feed one, feed two, and feed three. The Wilks and Roy tests also turned out to be significant differences for the intercept. All test measures showed significance for feed one. The Wilks and Roy tests also showed a significant difference for feed two, while all test measures found a significance for feed one. Another result showed that none of the tests found significance for the interaction between feed one and two, while the Roy test found significance for the interaction between feed one and three, feed two and three and feed one, two and three. The performance of the test for evaluating the performance of feeds for pig production with/without considering interactions was found to be in the following order of magnitude: Roy, Wilks and Pilla = LH. This result implies that the Roy method, with or without consideration of the interaction, has a better performance of the test than the other methods considered in the study.


Author(s):  
D.F. ANDREWS ◽  
R. GNANADESIKAN ◽  
J.L. WARNER

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