help mi estimate dialog: mi
also see: mi postestimation
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Title
[MI] mi estimate -- Estimation using multiple imputations
Syntax
Compute MI estimates of coefficients by fitting estimation command to mi
data
mi estimate [, options] : estimation_command ...
Compute MI estimates of transformed coefficients by fitting estimation
command to mi data
mi estimate [spec] [, options] : estimation_command ...
where spec may be one or more terms of the form ([name:] exp). exp is any
function of the parameter estimates allowed by nlcom.
options description
-------------------------------------------------------------------------
Main
nimputations(#) specify number of imputations to use;
default is to use all existing
imputations
imputations(numlist) specify which imputations to use
ufmitest perform unrestricted FMI model test
nosmall do not apply small-sample adjustment to
degrees of freedom
saving(miestfile[, replace]) save individual estimation results to
miestfile.ster
Tables
[no]citable suppress/display the standard estimation
table containing parameter-specific
confidence intervals; default is citable
dftable display the degrees-of-freedom table;
dftable implies nocitable
vartable display variance information about
estimates; vartable implies citable
table_options control table output
display_options control spacing and display of omitted
variables and base and empty cells
Reporting
level(#) set confidence level; default is level(95)
dots display dots as estimations performed
noisily display any output from estimation_command
(and from nlcom if transformations
specified)
trace trace estimation_command (and nlcom if
transformations specified); implies
noisily
nogroup suppress summary about groups displayed
for xt commands
xtme_options control output from mixed-effects commands
Advanced
esample(newvar) store estimation sample in variable
newvar; available only in the flong and
flongsep styles
errorok allow estimation even when
estimation_command (or nlcom) errors
out; such imputations are discarded from
the analysis
esampvaryok allow estimation when estimation sample
varies across imputations
cmdok allow estimation when estimation_command
is not one of the supported estimation
commands
+ coeflegend display coefficients' legend instead of
coefficient table
+ nowarning suppress the warning about varying
estimation sample
+ eform_option display coefficients table in
exponentiated form
+ post post estimated coefficients and VCE to
e(b) and e(V)
+ noupdate do not perform mi update; see [MI]
noupdate option
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+ coeflegend, nowarning, eform_option, post, and noupdate do not appear
in the dialog box.
You must mi set your data before using mi estimate; see [MI] mi set.
table_options description
-------------------------------------------------------------------------
noheader suppress table header(s)
notable suppress table(s)
nocoef suppress output related to coefficients
nocmdlegend suppress command legend that appears in
the presence of transformed coefficients
when nocoef is used
notrcoef suppress output related to transformed
coefficients
nolegend suppress table legend(s)
nocnsreport do not display constraints
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See [MI] mi estimate postestimation for features available after
estimation. mi estimate is its own estimation command. The
postestimation features for mi estimate do not include by default the
postestimation features for estimation_command. To replay results, type
mi estimate without arguments.
Menu
Statistics > Multiple imputation
Description
mi estimate: estimation_command runs estimation_command on the imputed mi
data, and adjusts coefficients and standard errors for the variability
between imputations according to the combination rules by Rubin (1987).
Options
+---------+
----+ Options +----------------------------------------------------------
nimputations(#) specifies that the first # imputations be used; # must be
2 <= # <= M. The default is to use all imputations, M. Only one of
nimputations() or imputations() may be specified.
imputations(numlist) specifies which imputations to use. The default is
to use all of them. numlist must contain at least two numbers. Only
one of nimputations() or imputations() may be specified.
ufmitest specifies that the unrestricted fraction missing information
(FMI) model test be used. The default test performed assumes equal
fractions of information missing due to nonresponse for all
coefficients. This is equivalent to the assumption that the
between-imputation and within-imputation variances are proportional.
The unrestricted test may be preferable when this assumption is
suspect provided the number of imputations is large relative to the
number of estimated coefficients.
nosmall specifies that no small-sample adjustment be made to the degrees
of freedom. The small-sample adjustment is made by default to
estimation commands that account for small samples. If the command
saves residual degrees of freedom in e(df_r), individual tests of
coefficients (and transformed coefficients) use the small-sample
adjustment of Barnard and Rubin (1999) and the overall model test
uses the small-sample adjustment of Reiter (2007). If the command
does not save residual degrees of freedom, the large-sample test is
used and the nosmall option has no effect.
saving(miestfile [, replace]) saves estimation results from each model
fit in miestfile.ster. The replace suboption specifies to overwrite
miestfile.ster if it exists. miestfile.ster can later be used by mi
estimate using (see [MI] mi estimate using) to obtain MI estimates of
coefficients or of transformed coefficients without refitting the
completed-data models. This file is written in the format used by
estimates use; see [R] estimates save.
+--------+
----+ Tables +-----------------------------------------------------------
All table options below may be specified at estimation time or when
redisplaying previously estimated results. Table options must be
specified as options to mi estimate, not to estimation_command.
citable and nocitable specify whether the standard estimation table
containing parameter-specific confidence intervals is displayed. The
default is citable. nocitable can be used with vartable to suppress
the confidence-interval table.
dftable displays a table containing parameter-specific degrees of freedom
and percentages of increase in standard errors due to nonresponse.
dftable implies nocitable.
vartable displays a table reporting variance information about MI
estimates. The table contains estimates of within-imputation
variances, between-imputation variances, total variances, relative
increases in variance due to nonresponse, fractions of information
about parameter estimates missing due to nonresponse, and relative
efficiencies for using finite M rather than a hypothetically infinite
number of imputations. vartable implies citable.
table_options control the appearance of all displayed table output:
noheader suppresses all header information from the output. The
table output is still displayed.
notable suppresses all tables from the output. The header
information is still displayed.
nocoef suppresses the display of tables containing coefficient
estimates. This option affects the output produced by citable,
dftable, and vartable.
nocmdlegend suppresses the table legend showing the specified command
line, estimation_command, from the output. This legend appears
above the tables containing transformed coefficients (or above
the variance-information table if vartable is used) when nocoef
is specified.
notrcoef suppresses the display of tables containing estimates of
transformed coefficients (if specified). This option affects the
output produced by citable, dftable, and vartable.
nolegend suppresses all table legends from the output.
nocnsreport; see [R] estimation options.
display_options: noomitted, vsquish, noemptycells, baselevels,
allbaselevels; see [R] estimation options.
+-----------+
----+ Reporting +--------------------------------------------------------
Reporting options must be specified as options to mi estimate and not as
options to estimation_command.
level(#); see [R] estimation options.
dots specifies that dots be displayed as estimations are successfully
completed. An x is displayed if the estimation_command returns an
error, if the model fails to converge, or if nlcom fails to estimate
one of the transformed coefficients specified in spec.
noisily specifies that any output from estimation_command and nlcom, used
to obtain the estimates of transformed coefficients if
transformations are specified, be displayed.
trace traces the execution of estimation_command and traces nlcom if
transformations are specified. trace implies noisily.
nogroup suppresses the display of group summary information (number of
groups, average group size, minimum, and maximum) as well as other
command-specific information displayed for xt commands.
xtme_options: variance, noretable, nofetable, estmetric; see, for
example, [XT] xtmixed. These options are relevant only with the
mixed-effects commands such as xtmixed, xtmelogit (see [XT]
xtmelogit), and xtmepoisson (see [XT] xtmepoisson). The estmetric
option is implied when vartable or dftable is used.
+----------+
----+ Advanced +---------------------------------------------------------
esample(newvar) creates newvar containing e(sample). This option is
useful to identify which observations were used in the estimation,
especially when the estimation sample varies across imputations (see
Potential problems that can arise when using mi estimate for
details). newvar is zero in the original data (m=0) and in any
imputations (m>0) in which the estimation failed or that were not
used in the computation. esample() may be specified only if the data
are flong or flongsep; see [MI] mi convert to convert to one of those
styles. The variable created will be super varying and therefore
must not be registered; see [MI] mi varying for more explanation.
The saved estimation sample newvar may be used later with mi extract
(see [MI] mi extract) to set the estimation sample.
errorok specifies that estimations that fail be skipped and the combined
results be based on the successful individual estimation results.
The default is that mi estimate stops if an individual estimation
fails. If errorok is specified with saving(), all estimation
results, including failed, are saved to a file.
esampvaryok allows estimation to continue even if the estimation sample
varies across imputations. mi estimate stops if the estimation
sample varies. If esampvaryok is specified, results from all
imputations are used to compute MI estimates and a warning message is
displayed at the bottom of the table. Also see the esample() option.
See Potential problems that can arise when using mi estimate for more
information.
cmdok allows unsupported estimation commands to be used with mi estimate;
see [MI] estimation for a list of supported estimation commands.
Alternatively, if you want mi estimate to work with your estimation
command, add the property mi to the program properties; see [P]
program properties.
The following options are available with mi estimate but are not shown in
the dialog box:
coeflegend; see [R] estimation options. coeflegend implies nocitable and
cannot be combined with citable or dftable.
nowarning suppresses the warning message at the bottom of table output
that occurs if the estimation sample varies and esampvaryok is
specified. See Potential problems that can arise when using mi
estimate for details.
eform_option; see [R] eform_option. Regardless of the estimation_command
specified, mi estimate reports results in the coefficient metric
under which the combination rules are applied. You may use the
appropriate eform_option to redisplay results in exponentiated form,
if desired. If dftable is also specified, the reported degrees of
freedom and percentage increases in standard errors are not adjusted
and correspond to the original coefficient metric.
post requests MI estimates of coefficients and their respective VCEs be
posted in the usual way. This allows the use of
estimation_command-specific postestimation tools with MI estimates.
There are issues; see Using the command-specific postestimation tools
in [MI] mi estimate postestimation. post may be specified at
estimation time or when redisplaying previously estimated results.
noupdate in some cases suppresses the automatic mi update this command
might perform; see [MI] noupdate option. This option is seldom used.
Example 1
Estimate on completed data using logit
. webuse mheart1s20
. mi describe
. mi estimate, dots: logit attack smokes age bmi hsgrad female
Replay estimation results
. mi estimate
Display coefficient-specific degrees of freedom
. mi estimate, dftable
Show coefficient-specific variance information
. mi estimate, vartable nocitable
Example 2
Estimate on completed data using stcox
. webuse mdrugtrs25
. mi describe
. mi stset studytime, failure(died)
. mi estimate, dots: stcox drug age
Redisplay results as hazard ratios
. mi estimate, hr
Example 3
Estimate on completed data of specified linear regression and
additionally specified transformation of those coefficients
. webuse mhouses1993s30
. mi estimate (ratio: _b[age]/_b[sqft]): regress price tax sqft age
nfeatures ne custom corner
Saved results
mi estimate saves the following in e():
Scalars
e(df_avg[_Q]_mi) average degrees of freedom
e(df_c_mi) complete degrees of freedom (if originally saved
by estimation_command in e(df_r))
e(df_max[_Q]_mi) maximum degrees of freedom
e(df_min[_Q]_mi) minimum degrees of freedom
e(df_m_mi) MI model test denominator (residual) degrees of
freedom
e(df_r_mi) MI model test numerator (model) degrees of
freedom
e(esampvary_mi) varying-estimation sample flag (0 or 1)
e(F_mi) model test F statistic
e(k_exp_mi) number of expressions (transformed coefficients)
e(M_mi) number of imputations
e(N_mi) number of observations (minimum, if varies)
e(N_min_mi) minimum number of observations
e(N_max_mi) maximum number of observations
e(N_g_mi) number of groups
e(g_min_mi) smallest group size
e(g_avg_mi) average group size
e(g_max_mi) largest group size
e(p_mi) MI model test p-value
e(rvi_avg[_Q]_mi) average RVI
e(rvi_avg_F_mi) average RVI associated with the residual degrees
of freedom for model test
e(ufmi_mi) 1 if unrestricted FMI model test is performed, 0
if equal FMI model test is performed
Macros
e(mi) mi
e(cmdline_mi) command as typed
e(prefix_mi) mi estimate
e(cmd_mi) name of estimation_command
e(title_mi) "Multiple-imputation estimates"
e(wvce_mi) title used to label within-imputation variance in
the table header
e(modeltest_mi) title used to label the model test in the table
header
e(dfadjust_mi) title used to label the degrees-of-freedom
adjustment in the table header
e(expnames_mi) names of expressions specified in spec
e(exp#_mi) expressions of the transformed coefficients
specified in spec
e(rc_mi) return codes for each imputation
e(m_mi) specified imputation numbers
e(m_est_mi) imputation numbers used in the computation
e(names_vvl_mi) command-specific e() macro names that contents
varied across imputations
e(names_vvm_mi) command-specific e() matrix names that values
varied across imputations
e(names_vvs_mi) command-specific e() scalar names that values
varied across imputations
Matrices
e(b) MI estimates of coefficients (equals e(b_mi),
saved only if post is used
e(V) variance-covariance matrix (equals e(V_mi), saved
only if post is used
e(Cns) constraint matrix (for constrained estimation
only; equals e(Cns_mi), saved only if post is
used)
e(N_g_mi) group counts
e(g_min_mi) group-size minimums
e(g_avg_mi) group-size averages
e(g_max_mi) group-size maximums
e(b[_Q]_mi) MI estimates of coefficients (or transformed
coefficients)
e(V[_Q]_mi) variance-covariance matrix (total variance)
e(Cns_mi) constraint matrix (for constrained estimation
only; equals e(Cns_mi), saved only if post is
used)
e(W[_Q]_mi) within-imputation variance matrix
e(B[_Q]_mi) between-imputation variance matrix
e(re[_Q]_mi) parameter-specific relative efficiencies
e(rvi[_Q]_mi) parameter-specific RVIs
e(fmi[_Q]_mi) parameter-specific FMIs
e(df[_Q]_mi) parameter-specific degrees of freedom
e(pise[_Q]_mi) parameter-specific percentages increase in
standard errors
e(vs_names_vs_mi) values of command-specific e() scalar vs_names
that varied across imputations
vs_names include (but are not restricted to) df_r, N, N_strata, N_psu,
N_pop, N_sub, N_poststrata, N_stdize, N_subpop, N_over, and
converged.
Results N_g_mi, g_min_mi, g_avg_mi, and g_max_mi are saved for panel-data
models only. The results are saved as matrices for mixed-effects
models and as scalars for other panel-data models.
If transformations are specified, the corresponding estimation results
are saved with the _Q_mi suffix, as described above.
Command-specific e() results that remain constant across imputations are
also saved. Command-specific results that vary from imputation to
imputation are posted as missing, and their names are saved in the
corresponding macros e(names_vvl_mi), e(names_vvm_mi), and
e(names_vvs_mi). For some command-specific e() scalars (see vs_names
above), their values from each imputation are saved in a
corresponding matrix with the _vs_mi suffix.
References
Barnard, J., and D. B. Rubin. 1999. Small-sample degrees of freedom with
multiple imputation. Biometrika 86: 948-955.
Reiter, J. P. 2007. Small-sample degrees of freedom for multi-component
significance tests with multiple imputation for missing data.
Biometrika 94: 502-508.
Rubin, D. B. 1987. Multiple Imputation for Nonresponse in Surveys. New
York: Wiley.
Also see
Manual: [MI] mi estimate
Help: [MI] mi estimate using, [MI] mi estimate postestimation, [MI] mi
