ParaARS.MIX {bear}R Documentation

Adjusted R squared (ARS) method and lme for parallel study

Description

Adjusted R squared (ARS) method: This method selects data points to estimate lambda(z) based on the maximun adjustedR squred values. It starts with the last three data points from the concentration-time course, performing log-linear regression to calculate the slope of that tail portion of the concentration-time curve. And then the last 4 data points, the last 5 data points, on and on until it excludes the data points of Cmax. Thus, this method may exclude the data point of (Tmax, Cmax). WNL v6. has the similar algoirthms like this.

With a two-treatment, two-sequence, one-period, parallel design, bear deploys the linear mixed effect model (lme). The statistical model includes a factor regarding only one source of variation - treatment. There are no sources of variation associated with sequence or period because there are no sequences or periods in a parallel design. Moreover, lme in nlme package is used to obtain estimates for the adjusted differences between treatment means and the standard error. Log-transformed BA measures will also be analyzed.


[Package bear version 2.3.0 Index]