LoBD: Cancer drug data use to provide an example of the use of the...

Description Usage Format Details Source References Examples

Description

A portion of an experiment to determine the limit of blank/limit of detection in a biochemical assay.

Usage

1

Format

A data frame with 84 observations on the following 9 variables.

pool

a factor with levels 1 2 3 4 5 6 7 8 9 10 11 12 denoting the 12 pools used in the experiment; each pool had a different level of drug.

I1L1

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I1L2

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I2L1

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I2L2

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I3L1

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I3L2

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I4L1

a numeric vector giving the measured concentration in pmol/L of drug in the assay

I4L2

a numeric vector giving the measured concentration in pmol/L of drug in the assay

Details

Important characteristics of a clinical chemistry assay are its limit of blank (LoB), and its limit of detection (LoD). The LoB, conceptually the highest reading likely to be obtained from a zero-concentration sample, is defined operationally by the upper 95% point of readings obtained from samples that do not contain the analyte. The LoD, conceptually the lowest level of analyte that can be reliably determined not to be blank, is defined operationally as true value at which there is a 95% chance of the reading being above the LoB.

These data are from a portion of a LoB/D study of an assay for a drug used to treat certain cancers. Twelve pools were used, four of them blanks of different types, and eight with successively increasing drug levels. The 8 columns of the data set refer to measurements made using different instruments I and reagent lots L.

Source

Used as an illustrative example for Box-Cox type transformations with negative readings in Hawkins and Weisberg (2015). For examples of its use, see bcnPower.

References

Hawkins, D. and Weisberg, S. (2015) Combining the Box-Cox Power and Generalized Log Transformations to Accommodate Negative Responses, submitted for publication.

Examples

1

carData documentation built on Nov. 24, 2017, 3:02 a.m.

Related to LoBD in carData...