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by
Fatehiboroujeni, Soheil, author.
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constitutive laws. The second contribution is the development of both deterministic and statistical inverse
by
Barnes, Sharon Pappas, author.
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Statistical methods used to analyze the data included descriptive statistics and independent t
by
Chati, Yashovardhan Sushil, author.
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important characteristic of statistical methods is that they provide both estimates of mean values, as well
by
Paulsson Do, Ulrica, author.
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), III (n=492) and IV (n=36). The quantitative data were analysed using a number of different statistical
by
DuBose, Wendy, author.
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majority students. A transformative explanatory sequential mixed methods design was employed to answer the
by
Kellermann, Anh Pham, author.
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treatments (MDTs) for handling missing data in complex sample surveys. The five missing data methods included
by
Piette, Elizabeth Rachel, author.
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quickly becomes nearly insurmountable with increasing numbers of loci. Statistical and machine learning
by
Chu, Chenghao, author.
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-sample statistical inference in both models, we studied the asymptotic properties of the proposed functional
by
Liang, Xiaoyu, author.
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, developing statistical methods to test for genetic association with multiple phenotypes has become
by
Carnell, Sue C., author.
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--15 were the focus of this study. The research methodology utilized for this study was a mixed methods
by
Wang, Zhenchuan, author.
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studies, we compared the performance of TOWmuT with the following five existing methods: gene association
by
Keele, Gregory R., author.
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that modulate complex phenotypes. Statistical methods developed for simpler populations have been

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