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

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.

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

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.

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).

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

See also

Slope

Examples

BestSlope(Theoph[Theoph$Subject==1, "Time"], Theoph[Theoph$Subject==1, "conc"])
#>         R2      R2ADJ    LAMZNPT       LAMZ         b0     CORRXY     LAMZLL 
#>  0.9999997  0.9999995  3.0000000  0.0484570  2.3687851 -0.9999999  9.0500000 
#>     LAMZUL      CLSTP 
#> 24.3700000  3.2801465 
BestSlope(Indometh[Indometh$Subject==1, "time"], Indometh[Indometh$Subject==1, "conc"],
          adm="Bolus")
#>          R2       R2ADJ     LAMZNPT        LAMZ          b0      CORRXY 
#>  0.99706673  0.99413345  3.00000000  0.15832048 -1.72421060 -0.99853229 
#>      LAMZLL      LAMZUL       CLSTP 
#>  5.00000000  8.00000000  0.05024851