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In addition to continuous scores, a binary variable was calculated for descriptive purposes using a cutoff score of ≥ 22.
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ORs for binary variables were calculated by using logistic regression.
A binary outcome variable was calculated, namely whether or not each of the live born child aged 12-23 months received all recommended doses of vaccination or not (child fully immunized = 0; child not fully immunized = 1) (endnote c).
This binary outcome variable was calculated for each health domain and for overall health.
A logistic regression model (GENMOD procedure in SAS) for the binary response variable was calculated in the first step of the two-part model predicting the odds ratio of positive expenditures in the respective obesity class.
Five-minute averages of each variable were calculated.
† Binary variable, OR was calculated using binary logistic regression.
Several variables were calculated on the binary images based on two-dimensional analysis.
The overall capacity variables are calculated for a simple ideal binary distillation column.
For TTCM, the trellises are non-binary and hence, in the Log-MAP operation all variables are calculated by means of the max∗ operator with n>2 arguments.
The ICCs for continuous and ordinal variables were calculated using multilevel package and ICC estimates for binary variables and boostrap confidence intervals were calculated using aod package in R. ICCs and 95% confidence intervals (CIs) were calculated for 429 heart failure patients (CP, n = 214 and UC, n = 215).
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