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We develop two enhanced techniques for the multilevel linear sampling method (MLSM) proposed in [32] for inverse scattering problems.
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In general, the estimation for multilevel linear regression models usually proceeds with the maximum likelihood method.
We use multilevel linear regression to estimate the determinants of trip length.
The shift schedule characteristics were analyzed separately and combined using multilevel linear regression models.
Data were analysed using multilevel linear regression.
The multilevel linear regression model explained 46.35% of the variance.
The primary analytic strategy was multilevel linear and logistic modeling.
Multilevel linear regression with imputed data (20 data sets).
Data were analyzed by multilevel linear mixed models.
Multilevel logistic regression was used to compare binary variables between groups, while multilevel linear regression was used for continuous variables.
For the primary and secondary outcome analyses, multilevel linear regression and multilevel logistic regression analyses will be used.
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