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Not only does the proposed algorithm process the whole message from two sides (which leads to high complexity in mixture), but also in the final step, instead of a simple XOR operation, a conditional method is used in order to resist forgery attack in any section of the algorithm.
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Variables significant on univariate analysis were entered into a multivariate model using a backwards conditional method.
Logistic regressions with a forward conditional method were run with the presence of a syndesmophyte (yes/no) and vertebral fracture (yes/no) as the binary outcome.
Predictors were included in each model analysis, and a backward conditional method was used for variable selection using logistic regression (categorical outcomes) or linear regression (continuous outcomes).
A forward conditional method was used.
The significant variables were selected using a forward conditional method.
A backward conditional method was used for variable selection in the adjusted model.
Logistic regression with a forward conditional method was run with low T-score (yes/no) as the binary outcome and the variables that were significantly correlated with BMD as covariates.
Initially, all covariates were entered into the model; covariates for the final model were selected by a forward conditional method with the probability of entry of 0.10 and of rejection of 0.15.
A backward conditional method was used for variable selection in the multivariable model including age, gender, T stage, N stage, M stage, differentiation grade, vascular invasion, MSI status, and KRAS and BRAF mutation status.
Hazard ratios (HRs) and 95% confidence intervals (CIs) were calculated for both RI and RSV-positive hospitalizations in premature infants ≤35 completed weeks GA who met standard approval criteria (group 1) compared to those with medical disorders (group 2) using Cox proportional hazards regression models with adjustment for potential confounding factors using a backward conditional method.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com