Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test
Normality and homogeneity are two major assumptions that need to be fulfilled when using independent sample t-test. However, not all data encompassed with these assumptions. Consequently, the result produced by independent sample t-test becomes invalid. Therefore, the alternative is to use robust st...
| Main Authors: | , |
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| Format: | Conference or Workshop Item |
| Language: | English |
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2014
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| Online Access: | https://repo.uum.edu.my/id/eprint/30926/1/ICOQSIA%201635%2001%202014%20755-761.pdf |
| _version_ | 1825806269718462464 |
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| author | Harun, Nurul Hanis Md Yusof, Zahayu |
| author_facet | Harun, Nurul Hanis Md Yusof, Zahayu |
| author_sort | Harun, Nurul Hanis |
| collection | UUM |
| description | Normality and homogeneity are two major assumptions that need to be fulfilled when using independent sample t-test. However, not all data encompassed with these assumptions. Consequently, the result produced by independent sample t-test becomes invalid. Therefore, the alternative is to use robust statistical procedure in handling the problems of nonnormality and variances heterogeneity. This study proposed to use Parametric Bootstrap test with popular robust estimators, MADn and Tn which empirically determines the amount of trimming. The Type I error rates produced by each procedure were examined and compared with classical parametric test and nonparametric test namely independent sample t-test and Mann Whitney test, respectively. 5000 simulated data sets are used in this study in order to generate the Type I error for each procedure. The findings of this study indicate that the Parametric Bootstrap test with MADn and Tn produces the best Type I error control compared to the independent sample t-test and the Mann Whitney test under nonnormal distribution, heterogeneous variances and unbalanced design. Then, the performance of each procedure was demonstrated using real data |
| first_indexed | 2024-07-04T06:46:50Z |
| format | Conference or Workshop Item |
| id | uum-30926 |
| institution | Universiti Utara Malaysia |
| language | English |
| last_indexed | 2024-07-04T06:46:50Z |
| publishDate | 2014 |
| record_format | eprints |
| spelling | uum-309262024-06-23T09:31:38Z https://repo.uum.edu.my/id/eprint/30926/ Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test Harun, Nurul Hanis Md Yusof, Zahayu QA Mathematics Normality and homogeneity are two major assumptions that need to be fulfilled when using independent sample t-test. However, not all data encompassed with these assumptions. Consequently, the result produced by independent sample t-test becomes invalid. Therefore, the alternative is to use robust statistical procedure in handling the problems of nonnormality and variances heterogeneity. This study proposed to use Parametric Bootstrap test with popular robust estimators, MADn and Tn which empirically determines the amount of trimming. The Type I error rates produced by each procedure were examined and compared with classical parametric test and nonparametric test namely independent sample t-test and Mann Whitney test, respectively. 5000 simulated data sets are used in this study in order to generate the Type I error for each procedure. The findings of this study indicate that the Parametric Bootstrap test with MADn and Tn produces the best Type I error control compared to the independent sample t-test and the Mann Whitney test under nonnormal distribution, heterogeneous variances and unbalanced design. Then, the performance of each procedure was demonstrated using real data 2014 Conference or Workshop Item PeerReviewed application/pdf en https://repo.uum.edu.my/id/eprint/30926/1/ICOQSIA%201635%2001%202014%20755-761.pdf Harun, Nurul Hanis and Md Yusof, Zahayu (2014) Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test. In: International Conference on Quantitative Sciences and Its Applications (ICOQSIA 2014), 12–14 August 2014, Langkawi, Kedah Malaysia. http://dx.doi.org/10.1063/1.4903667 |
| spellingShingle | QA Mathematics Harun, Nurul Hanis Md Yusof, Zahayu Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test |
| title | Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test |
| title_full | Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test |
| title_fullStr | Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test |
| title_full_unstemmed | Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test |
| title_short | Robust Parametric Bootstrap Test with MOM Estimator: An Alternative to Independent Sample t-Test |
| title_sort | robust parametric bootstrap test with mom estimator an alternative to independent sample t test |
| topic | QA Mathematics |
| url | https://repo.uum.edu.my/id/eprint/30926/1/ICOQSIA%201635%2001%202014%20755-761.pdf |
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