help jackknife dialog: jackknife
also see: jackknife postestimation
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Title
[R] jackknife -- Jackknife estimation
Syntax
jackknife exp_list [, options eform_option ] : command
options description
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Main
eclass number of observations used is stored in e(N)
rclass number of observations used is stored in r(N)
n(exp) specify exp that evaluates to the number of
observations used
Options
cluster(varlist) variables identifying sample clusters
idcluster(newvar) create new cluster ID variable
saving(filename, ...) save results to filename; save statistics in
double precision; save results to filename
every # replications
keep keep pseudovalues
mse use MSE formula for variance estimation
Reporting
level(#) set confidence level; default is level(95)
notable suppress table of results
noheader suppress table header
nolegend suppress table legend
verbose display the full table legend
nodots suppress the replication dots
noisily display any output from command
trace trace the command
title(text) use text as title for jackknife results
display_options control spacing and display of omitted
variables and base and empty cells
Advanced
nodrop do not drop observations
reject(exp) identify invalid results
+ eform_option display coefficient table in exponentiated
form
+ coeflegend display coefficients' legend instead of
coefficient table
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+ eform_option and coeflegend do not appear in the dialog box.
svy is allowed; see [SVY] svy jackknife.
All weight types supported by command are allowed except aweights; see
weight.
See [R] jackknife postestimation for features available after estimation.
Menu
Statistics > Resampling > Jackknife estimation
Description
jackknife performs jackknife estimation. Typing
. jackknife exp_list: command
executes command once for each observation in the dataset, leaving the
associated observation out of the calculations that make up exp_list.
command defines the statistical command to be executed. Most Stata
commands and user-written programs can be used with jackknife, as long as
they follow standard Stata syntax and allow the if qualifier. The by
prefix may not be part of command; see [U] 11 Language syntax.
exp_list specifies the statistics to be collected from the execution of
command. If command changes the contents in e(b), exp_list is optional
and defaults to _b.
Many estimation commands allow the vce(jackknife) option. For those
commands, we recommend using vce(jackknife) over jackknife because the
estimation command already handles clustering and other model-specific
details for you. The jackknife prefix command is intended for use with
nonestimation commands, such as summarize, user-written commands, or
functions of coefficients.
jknife is a synonym for jackknife.
Options
+------+
----+ Main +-------------------------------------------------------------
eclass, rclass, and n(exp) specify where command saves the number of
observations on which it based the calculated results. We strongly
advise you to specify one of these options.
eclass specifies that command save the number of observations in
e(N).
rclass specifies that command save the number of observations in
r(N).
n(exp) specifies an expression that evaluates to the number of
observations used. Specifying n(r(N)) is equivalent to specifying
the rclass option. Specifying n(e(N)) is equivalent to specifying
the eclass option. If command saved the number of observations in
r(N1), specify n(r(N1)).
If you specify no options, jackknife will assume eclass or rclass,
depending on which of e(N) and r(N) is not missing (in that order).
If both e(N) and r(N) are missing, jackknife assumes that all
observations in the dataset contribute to the calculated result. If
that assumption is incorrect, the reported standard errors will be
incorrect. For instance, say that you specify
. jackknife coef=_b[x2]: myreg y x1 x2 x3
where myreg uses e(n) instead of e(N) to identify the number of
observations used in calculations. Further assume that observation
42 in the dataset has x3 equal to missing. The 42nd observation
plays no role in obtaining the estimates, but jackknife has no way of
knowing that and will use the wrong N. If, on the other hand, you
specify
. jackknife coef=_b[x2], n(e(n)): myreg y x1 x2 x3
jackknife will notice that observation 42 plays no role. The n(e(n))
option is specified because myreg is an estimation command but it
saves the number of observations used in e(n) (instead of the
standard e(N)). When jackknife runs the regression omitting the 42nd
observation, jackknife will observe that e(n) has the same value as
when jackknife previously ran the regression using all the
observations. Thus jackknife will know that myreg did not use the
observation.
+---------+
----+ Options +----------------------------------------------------------
cluster(varlist) specifies the variables identifying sample clusters. If
cluster() is specified, one cluster is left out of each call to
command, instead of 1 observation.
idcluster(newvar) creates a new variable containing a unique integer
identifier for each resampled cluster, starting at 1 and leading up
to the number of clusters. This option may be specified only when
the cluster() option is specified. idcluster() helps identify the
cluster to which a pseudovalue belongs.
saving(filename [, suboptions]) creates a Stata data file (.dta file)
consisting of (for each statistic in exp_list) a variable containing
the replicates.
See prefix_saving_option for details about suboptions.
replace specifies that filename be overwritten, if it exists. This
option is not shown in the dialog box.
keep specifies that new variables are to be added to the dataset
containing the pseudovalues of the requested statistics. See
[R] jackknife for details. When the cluster() option is specified,
each cluster is given at most one nonmissing pseudovalue. This
option implies the nodrop option.
mse specifies that jackknife compute the variance by using deviations of
the replicates from the observed value of the statistics based on the
entire dataset. By default, jackknife computes the variance by using
deviations of the pseudovalues from their mean.
+-----------+
----+ Reporting +--------------------------------------------------------
level(#); see [R] estimation options.
notable suppresses the display of the table of results.
noheader suppresses display of the table header. This option implies
nolegend.
nolegend suppresses display of the table legend. The table legend
identifies the rows of the table with the expressions they represent.
verbose specifies that the full table legend be displayed. By default,
coefficients and standard errors are not displayed.
nodots suppresses display of the replication dots. By default, one dot
character is displayed for each successful replication. A red `x' is
displayed if command returns an error or if one of the values in
exp_list is missing.
noisily specifies that any output from command be displayed. This option
implies the nodots option.
trace causes a trace of the execution of command to be displayed. This
option implies the noisily option.
title(text) specifies a title to be displayed above the table of
jackknife results; the default title is Jackknife results or what is
produced in e(title) by an estimation command.
display_options: noomitted, vsquish, noemptycells, baselevels,
allbaselevels; see [R] estimation options.
+----------+
----+ Advanced +---------------------------------------------------------
nodrop prevents observations outside e(sample) and the if and in
qualifiers from being dropped before the data are resampled.
reject(exp) identifies an expression that indicates when results should
be rejected. When exp is true, the resulting values are reset to
missing values.
The following options are available with jackknife but are not shown in
the dialog box:
eform_option causes the coefficient table to be displayed in
exponentiated form; see [R] eform_option. command determines which
eform_option is allowed (eform(string) and eform are always allowed).
coeflegend; see [R] estimation options.
Examples
Setup
. sysuse auto
Jackknifed standard error of the sample mean
. jackknife r(mean): summarize mpg
Jackknifed standard errors of the coefficients from a regression
. jackknife: regress mpg weight trunk
Saved results
jknife saves the following in e():
Scalars
e(N) sample size
e(N_reps) number of complete replications
e(N_misreps) number of incomplete replications
e(N_clust) number of clusters
e(df_r) degrees of freedom
Macros
e(cmdname) command name from command
e(cmd) same as e(cmdname) or jackknife
e(command) command
e(cmdline) command as typed
e(prefix) jackknife
e(wtype) weight type
e(wexp) weight expression
e(title) title in estimation output
e(cluster) cluster variables
e(pseudo) new variables containing pseudovalues
e(nfunction) e(N), r(N), n() option, or empty
e(exp#) expression for the #th statistic
e(mse) from mse option
e(vce) jackknife
e(vcetype) title used to label Std. Err.
e(properties) b V
Matrices
e(b) observed statistics
e(b_jk) jackknife estimates
e(V) jackknife variance-covariance matrix
e(V_modelbased) model-based variance
When exp_list is _b, jackknife will also carry forward most of the
results already in e() from command.
Also see
Manual: [R] jackknife
Help: [R] jackknife postestimation;
[R] bootstrap, [R] permute, [R] simulate, [SVY] svy jackknife
