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Datasets were examined with confirmatory factor analysis, model invariance testing and systematic evaluation of relational and internal aspects of the measure.
The four datasets were examined separately by fitting linear mixed models to the variables of interest, namely timber volume and the LiDAR variables OV and CC (Turner et al. 2011).
Four types of simulated datasets were examined.
The beta diversity patterns within the four datasets were examined using various qualitative and quantitative similarity indices.
Sequence input order was randomized, and 100 datasets were examined by bootstrapping resampling statistics.
Nine accessions present in both datasets were examined for differences in allele calls (Table 1).
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These datasets are examined in both their original and standardized forms.
ConTra's capability to enable the identification of contradictory data in different sizes of datasets is examined.
Two real-world P2P lending datasets are examined, and explanatory data analysis shows that explanatory variables differ in predicting the probability of default and profitability.
The stationarity of the datasets was examined by applying two commonly used methods, the Phillips-Perron (PP) test (Phillips and Perron 1988) and the augmented Dickey-Fuller (ADF) test (Dickey and Fuller 1979).
The expression of gene signatures from a number of publicly available datasets was examined in normal tissue.
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