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Measurement data obtained from an inspection system need to be analyzed using appropriate algorithms to estimate dimensional errors and to obtain reliable inspection results.
For secondary outcomes, the four groups will be analyzed using appropriate modelling, such as linear regression, when the data are normal and logistic regression when the data are dichotomous.
Further longitudinal data regarding outcomes of markers of renal and hepatic function, overall survival and e.g. kidney size will be analyzed using appropriate statistical methods such as mixed modeling.
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The structural phase composition and the morphology of the samples were analyzed using appropriate powder characterization methods.
The effect of location of crack along the thickness of the plate on natural frequencies is analyzed using appropriate crack compliance coefficients in the Line Spring Model.
Data were analyzed using appropriate statistical methods in R [25].
Data were analyzed using appropriate descriptive, univariate and multivariable logistic regression methods.
Data were analyzed using appropriate non-parametric tests.
Characterization of tumor growth was analyzed using appropriate statistical methods.
The distributions of half-life values and protein disorder were analyzed using appropriate statistical tests.
To account for the complex sampling design, data were analyzed using appropriate NHANES sample weights using the "svy" command in Stata version 12.1 (StataCorp, College Station, TX).
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