Ne_up: Upper 1-alpha Confidence Bound (Minimum Sum Method)

In mncube/claimr: What the Package Does (One Line, Title Case)

Description

Function obtained from Edwards et. al. (2003): "a bisection routine to find an upper 1-alpha confidence bound for Ne, the number of population items in error. Population size Npop, SRS size nsamp, ne = number of sample items in error."

Usage

Ne_up(Npop, nsamp, ne, alpha = 0.1)

Arguments

Npop	"Number of payments (e.g. on Medicare claims) in the universe/population"
nsamp	"Number of payments (e.g. on Medicare claims) in...simple random sample"
ne	"The number...of sample payments which are completely in error (Or, for partial overpayment scenarios, seriously in error—see Section 4.2.)"
alpha	alpha-level for "1-alpha confidence bound"

Details

Citation: Edwards, D., Ward-Besser, G., Lasecki, J., Parker, B., Wu, F. & Moorhead, P. (2003). The Minimum Sum Method: A Distribution-Free Sampling Procedure for Medicare Fraud Investigations. Heath Services & Outcomes Research Methodology 4: 241-263.

Value

Upper 1-alpha confidence bound for the "number...of universe payments which are completely in error (Or, for partial overpayment scenarios, seriously in error—see Section 4.2.)"

Examples

Ne_up(Npop = 1000, nsamp = 30, ne = 15, alpha=0.05)

mncube/claimr documentation built on Dec. 21, 2021, 8:07 p.m.