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A three-parameter Weibull primary model was used to describe survival kinetics.
To overcome such shortcoming, the primary model was then extended by introducing a new variable FP to address the effect of cyclic softening feature.
In the next step the primary model was designed using the components and indexes resulted from the second research step and merging the same with the experiences of some of the hospitals offering preventive and health promotion services in the selected countries and the same model was then finalized within two Delphi steps.
The primary model was adjusted for age, sex, body mass index, diabetes, antihypertensive use, and lipid lowering drug use.
The primary model was estimated with complete cases for each set of tasks, meaning that information was reported on each task within a set.
One outlier with a standardized residual of -2.93 in the primary model was removed from the data prior to building the final model.
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While the primary model is specified correctly, it is important to perform checks on the robustness of such a model to ensure that our results are consistent across multiple specifications, which are reported in Tables 6 and 7.
The primary model is that the loss of D4Z4 repeats increases expression of a double homeobox transcription factor DUX4c, a putative gene centromeric to the D4Z4 repeats and highly homologous to DUX4 [12], [13], [13].
Thus, based on mixed linear models, our primary model is based on analysis of covariance for continuous end points.
Participants (n=36) with protocol violations or missing data required for the primary model were excluded (n=1543 analysed vs n=1579).
Our primary model is a Bayesian Markov model that incorporates uncertainty associated with the clinical input data (eg, adverse event rates).
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CEO of Professional Science Editing for Scientists @ prosciediting.com