Description Usage Arguments Details Value Examples
View source: R/minimum_sum_method.R
"LMS = sum of the ne sample overpayments + sum of the smallest LNE - ne nonsampled population payments"
1 |
df_samp |
Sample (must have var, flag, and sub_var) |
df_frame |
sampling frame (must have sub_var variable to match with df_samp) |
var |
Independent variable in LMS calculation |
sub_var |
Variable used to match sample records (df_samp) and sampling frame records (df_frame) |
flag |
Variable that flags observations with errors. |
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" |
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.
LMS nested list returning a list of numbers and a list of data_frames
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 | #Generate sampling frame with an index id from 1 to N
df_sample_frame_num <- data.frame("sample_frame_sequence_id" = 1:1000,
"score" = rnorm(1000, 75, 10))
#Get output and input in lists
score_audit_num <- rs_singlestage(df = df_sample_frame_num,
audit_review = "Score Audit",
quantity_to_generate = 100,
quantity_of_spares = 3,
frame_low = 1,
frame_high = 1000)
score_samp <- score_audit_num$output$sample
score_samp$audit_results <- sample(0:1, 100, replace = TRUE)
score_frame <- score_audit_num$output$sample_frame
LMS_out <- LMS(score_samp, score_frame, var = score, sub_var = sample_frame_sequence_id,
flag = audit_results,
Npop = 1000, nsamp = 100, ne = 100)
#Get LMS estimate
LMS_out$numbers$LMS
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