[SVY] jkstat -- Reporting jackknife results
jkstat [varlist] [weight] [if] [in] [, options ]
jkstat [namelist] [using filename] [if] [in] [, options ]
notable suppress table of output
noheader suppress table header
nolegend suppress table legend
verbose display the full table legend
level(#) confidence level for CIs
title(text) title for jackknife results
stat(vector) observed values
mse use MSE formula for variance estimate
display_options control column formats
fweights, pweights, and iweights are allowed with jkstat; see weight.
jkstat shares the features of all estimation commands, except that
adjust, margins, predict, and predictnl are not allowed; see estcom.
jkstat is a programmer's command that computes and displays estimation
results from jackknife statistics.
jkstat computes a variance-covariance matrix using the variables in
varlist, assuming the variables contain replicate values from a jackknife
If given the using modifier, jkstat will use the data in filename to
perform its calculations while preserving the data currently in memory.
The data in memory are used by default.
The following options may be used when replaying estimation results from
level(#) notable noheader nolegend verbose title(text)
For all other options (and qualifiers using, if, and in), jkstat requires
notable prevents displaying the output table. This option implies
noheader suppresses the displaying of the table header. This option
nolegend suppresses the displaying of the table legend. The table legend
identifies the rows of the table with the expressions they represent.
verbose requests that the full table legend be displayed. By default,
coefficients and standard errors are not displayed.
level(#); see estimation_options.
title(text) specifies a title to be displayed above the table of
jackknife results; the default title is "Jackknife statistics".
stat(vector) allows the user to specify the observed value of each
statistic (that is, the value of the statistic using the original
strata(varname) specifies the variable that contains the stratum
mse specifies that jkstat compute the variance by using deviations of the
replicates from the observed value of the statistics based on the
entire dataset. By default, jkstat computes the variance by using
deviations of the pseudovalues from their mean.
display_options: cformat(%fmt), pformat(%fmt), and sformat(%fmt); see
[R] estimation options.
Although jkstat allows users to specify the observed value and stratum
identifier of each jackknife statistic via the stat() and strata()
options, programmers may be interested in what jkstat uses when these
options are not supplied.
When working from a jackknife dataset, jkstat first checks the data
characteristics (see [P] char). Here is a list of the characteristics
that jkstat understands:
_dta[jk_version] identifies the version of the jackknife dataset. This
characteristic is assumed to be empty (not defined) or 1; otherwise
jkstat will behave as if it were empty. This version informs jkstat
which other characteristics to look for in the jackknife dataset.
jkstat uses the following characteristics from version 1 jackknife
An empty jackknife dataset version implies that the dataset was not
created by jackknife. Here the stat() option is required. All other
characteristics are ignored.
_dta[N] is the number of observations in the observed dataset.
_dta[N_cluster] is the number of clusters in the observed dataset.
_dta[command] is the command used to compute the observed values of the
_dta[jk_svy] identifies that the jackknife data came from survey data
when is contains "svy"; otherwise, nonsurvey data is assumed. When
this characteristic is appropriately set, it causes jkstat to look
for the following other characteristics:
_dta[psu] _dta[wtype] _dta[wexp] _dta[rweights]
_dta[names] identifies the variables containing the jackknife replicates.
varname[observed] is the observed value of the statistic identified by
varname. This characteristic may be overruled by specifying the
varname[expression] is the expression or label that describes the
statistic identified by varname.
The following characteristics are available only when _dta[jk_svy] is
_dta[N_strata] is the number of strata in the observed dataset.
_dta[N_psu] is the number of PSUs in the observed dataset.
_dta[strata] is the name of the variable from the original dataset that
identifies the strata. This characteristic will usually contain the
same variable name as _dta[jk_strata].
_dta[jk_strata] is the name of the variable that identifies the strata.
This characteristic may be overruled by specifying the strata()
_dta[jk_multiplier] is the name of the variable that contains multiplier
values used in the jackknife variance formula. This characteristic
can be overruled by specifying weight.
_dta[psu] is the name of the variable from the original dataset that
identifies the primary sampling units.
_dta[wtype], _dta[wexp], and _dta[rweights] identify the weight type,
expression, and list of replicate weight variable names from the
observed dataset. _dta[wtype] and _dta[wexp] may also be set for
nonsurvey data, but this is only advisable with fweights; see
jkstat stores the following in e():
e(N) sample size
e(N_strata) number of strata
e(N_cluster) number of clusters (for nonsurvey data)
e(N_psu) number of PSUs (for survey data)
e(N_reps) number of requested replications
e(command) command from _dta[command]
e(exp#) expression for the #th statistic
e(strata) strata variable
e(cluster) cluster variable
e(missing) "missing" if missing values found, otherwise empty
e(varlist) varlist or namelist
e(vcetype) "Jackknife" or "Jknife *"
e(mse) "mse" if mse option supplied
e(b) observed statistics
e(V) jackknife variance matrix
e(jk_b) jackknife means