FG_CP: FG_CP

In ciccr: Causal Inference in Case-Control and Case-Population Studies

FG_CP

Description

Case-population sample extracted from Fang and Gong (2020). The case-population sample is extracted from Fang and Gong (2020) by the following procedure. The case sample is composed of 2,261 flagged physicians (that is, those who billed for more than 100 hours per week). The control sample of equal size is randomly drawn without replacement from all observations and its flagged status is coded missing. The sample is composed of 4,522 physicians who billed at least 20 hours per week.

Usage

FG_CP

Format

A data frame with 4,522 rows and 5 variables:

male

indicator: physician is male

isMD

indicator: physician has a MD degree

experYear

experience in years

flag

1 if an observation belongs to the case sample; NA otherwise

smallPractice

indicator: number of group practice members less than 6

Source

Fang, H. and Gong, Q. (2020) Data and Code for: Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Reply. Nashville, TN: American Economic Association [publisher]. Ann Arbor, MI: Inter-university Consortium for Political and Social Research [distributor], 2020-11-23. \Sexpr[results=rd]{tools:::Rd_expr_doi("10.3886/E119192V1")}

References

Fang, H. and Gong, Q. (2017). Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked. American Economic Review, 107(2), 562-91.

Matsumoto, B. (2020). Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Comment. American Economic Review, 110(12), 3991-4003.

Fang, H. and Gong, Q. (2020). Detecting Potential Overbilling in Medicare Reimbursement via Hours Worked: Reply. American Economic Review, 110(12): 4004-10.

ciccr documentation built on Oct. 21, 2023, 1:08 a.m.