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The difference between the models using the inclusion size is that one is based on the assumption that the specimen breaks in the largest inclusion, and the other one on the assumption that the specimen breaks in some inclusion over a critical size, not necessarily the largest one.
MI and NF were compared between the models using the independent samples t test.
We controlled for differences in size between the models using a recently developed method for comparing FE models [16].
The measurement of accuracy can be compared between the models using RMSE and sigma.
Since coefficient and standard error estimates did not change substantially between the models using independent, exchangeable, and unstructured covariance between the random slopes and intercepts, independent covariance was specified in the final models for simplicity.
We evaluated the statistical significance of model parameters, test of trend, and comparison in goodness of fit between the models using likelihood ratio chi-square test with degrees of freedom (df) equal to the difference in number of parameters in compared models.
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We developed autoregressive integrated moving average (ARIMA) models on the data collected between 1985 to 1994, and then validated the models using the data collected between 1995 and 1996.
We use the conceptual tool of holon from complexity theory to provide a link between the models used for the governance of nuclear power and the realization of those models.
Of great interest is the possible overlap in miRNA deregulation between the models used in our study with the existing profiling studies performed on human AD brain (Table 1).
This apparent discrepancy may be due to the differences between the models used.
The major difference between the models used for the LBD and the full receptor is the lack of protein concentration dependence for formation of the dimeric state.
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