pkr (version 0.1.6)

BestSlope: Choose best fit slope for the log(y) and x regression by the criteria of adjusted R-square

Description

It sequentially fits (log(y) ~ x) from the last point of x to the previous points with at least 3 points. It chooses a slope the highest adjusted R-square. If the difference is less then 1e-4, it chooses longer slope.

Usage

BestSlope(x, y, adm = "Extravascular", TOL=1e-4)

Value

R2

R-squared

R2ADJ

adjusted R-squared

LAMZNPT

number of points used for slope

LAMZ

negative of slope, lambda_z

b0

intercept of regression line

CORRXY

correlation of log(y) and x

LAMZLL

earliest x for lambda_z

LAMZUL

last x for lambda_z

CLSTP

predicted y value at last point, predicted concentration for the last time point

Arguments

x

vector values of x-axis, usually time

y

vector values of y-axis, usually concentration

adm

one of "Bolus" or "Infusion" or "Extravascular" to indicate drug administration mode

TOL

tolerance. See Phoneix WinNonlin 6.4 User's Guide p33 for the detail.

Author

Kyun-Seop Bae <[e-mail]>

Details

Choosing the best terminal slope (y in log scale) in pharmacokinetic analysis is somewhat challenging, and it could vary by analysis performer. Pheonix WinNonlin chooses a slope with highest adjusted R-squared and the longest one. Difference of adjusted R-Squared less than TOL considered to be 0. This function uses ordinary least square method (OLS).

See Also

Slope

Examples

BestSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
BestSlope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"],
          adm="Bolus")