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We selected the covariance structure of the repeated-measures variable by inspection of the covariance matrix and by the use of information criteria of the model as a whole.
The key idea is to propagate the effect of time invariant stochastic uncertainties onto the measured variables by using a Generalized Polynomial Chaos (gPC) expansion and the nonlinear first principles' model of the process.
The primary purpose of exploratory factor analysis (EFA) is to arrive at a more parsimonious conceptual understanding of a set of measured variables by determining the number and nature of common factors needed to account for the pattern of correlations among the measured variables (Fabrigar et al. 1999).
We shall analyse most other measured variables by mixed-model analysis of variance (ANOVA).
We will present the level of balance at baseline by summarising important measured variables by arm, and will assess the magnitude of any differences.
Soft sensor is an efficacious solution to predict the hard-to-measure target variable by using the process variables.
Distribution of each measured variable was assessed by PROC UNIVARITE/SAS SAS Institutee, Inc. Cary, NC).
Items in italics omitted from exploratory analysis of a new attitudinal scale † The extent that the variance of the measured variable is explained by the latent factor.
Examples of additional items in italics † The extent that the variance of the measured variable is explained by the latent factor.
The effect of L-NMMA on repeatedly measured variables was assessed by Friedman's two-way ANOVA.
Firstly, we collected data in 3 months– March, April and May in 2016, also from the "CMKT Management Club 2 community", and measured all variables by a time unit of 1 week.
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