help for rsens

Sensitivity analysis after matching with multiple nearest neighbours

rsens
outcomevar
,
gamma(numlist)
nn(integer)
[treatment(varname)
id(varname)
matchid(namelist)
support(varname)]

Description

rsens calculates Rosenbaum sensitivity bounds following nearest neighbour matching with up to 20 nearest neighbours. While not mandatory, it is designed to be used after psmatch2, as detailed below.

rsens implements the procedure described by Rosenbaum (2002) to calculate bounds on the significance level for the treatment effect calculated using nearest neighbour matching, based on a signed rank statistic.

Basic Syntax

(if used after psmatch2)

rsens
outcomevar
,
gamma(numlist)
nn(integer)

outcomevar is required, and specifies the variable name of the outcome for which treatment effects are being calculated.

gamma(numlist) is required, and specifies the values of Gamma at which Rosenbaum's
sensitivity bounds are to be calculated. numlist must contain 1, the level of Gamma at which allocation
to treatment is assumed to be independent of unobservables.

nn(integer) is required, and specifies the number of nearest neighbours with which matching was undertaken.

Options

rsens requires outcomevar, gamma(numlist) and nn(integer) to be specified if used after nearest neighbour matching undertaken with psmatch2. Otherwise, the following options might need to be specified.

rsens
outcomevar
,
gamma(numlist)
nn(integer)
treatment(varname)
id(varname)
matchid(varname)
support(varname)

Where

treatment(varname) provides the binary indicator for allocation to treatment. The default varname generated by psmatch2 is _treated.

id(varname) provides the identifier used to specify matches. The default varname generated by psmatch2 is _id.

matchid(namelist) specifies, for each treatment observation, the prefix for a list of variable names of the form var1, var2, var3... that identify matched control observations according to id(varname). For instance, matching on the nearest 3 neighbours and specifying matchid( mymatch) implies that the dataset should contain three variables mymatch1, mymatch2 and mymatch3 that identify, for each treatment observation, the matched control observations using id(varname) as the identifier.
The default varname generated by psmatch2 is _n, as in _n1, _n2, _n3 for nearest 3 neighbour matching.

support(varname) is an indicator variable that specifies the region of common support used in the matching exercise. The default varname generated by psmatch2 is _support.

The results of rsens are returned in r(rsensresult).

Example

In the following, collgrad is the binary treatment and the outcome is wage.

. sysuse nlsw88.dta, clear
. psmatch2 collgrad age race married, outcome(wage) n(2)
. rsens wage, gamma(1(0.5)4) nn(2)

References

Rosenbaum, P.R. (2002) Observational Studies. 2nd edition. New York: Springer.

Author

Sunil Mitra Kumar, King's College London; stuff.sunil@gmail.com