equivalent_n {NADA2} | R Documentation |
Censored data sample size
Description
Computes the equivalent sample size of censored data. Observations at lower detection limits have a greater percent of the equivalent information of a detected value than observations at higher detection limits.
Usage
equivalent_n(y.var, y.cen, printstat = TRUE)
Arguments
y.var |
The column of data values plus detection limits. |
y.cen |
The column of indicators, where 1 (or |
printstat |
Logical |
Details
Based on "Method 2" of Dr. Brenda Gillespie's talk at ASA National Meeting 2019. This method differs from hers in how the percentile probabilities for the detection limits are computed. Probabilities here are computed using Regression on Order Statistics (ROS).
Computes the equivalent n, the number of observations including censored values, as a measure of information content for data with nondetects.
Value
Prints summary statistics including
-
n
sample size -
n.cen
number of censored data -
pct.cen
percent of data censored -
min
minimum reported value -
max
maximum reported value
Summary of censored data including
-
limit
detection limit -
n
number of censored values per limit -
uncen
number of detected values at or above the limit -
pexceed
proportion of data that exceeds the limit
Summary of the equivalent sample size for detected and censored values.
-
n.equiv
the equivalent number of observations -
n.cen.equiv
equivalent number of detected obs in the censored data -
n.detected
number of uncensored values
References
Helsel, D.R., 2011. Statistics for Censored Environmental Data using Minitab and R, 2nd ed. John Wiley & Sons, USA, N.J.
Gillespie, B.W., Dominguez, A., Li, Y., 2019. Quantifying the information in values below the detection limit (left-censored data). Presented at the 2019 Joint Statistical Meetings of the Amer. Stat. Assoc., Denver, CO., July 31, 2019.
See Also
Examples
data(Brumbaugh)
equivalent_n(Brumbaugh$Hg,Brumbaugh$HgCen)