**[R] bstat** -- Report bootstrap results

__Syntax__

Bootstrap statistics from variables

**bstat** [*varlist*] [*if*] [*in*] [**,** *options*]

Bootstrap statistics from file

**bstat** [*namelist*] [**using** *filename*] [*if*] [*in*] [**,** *options*]

*options* Description
-------------------------------------------------------------------------
Main
* __s__**tat(***vector***)** observed values for each statistic
* **accel(***vector***)** acceleration values for each statistic
* __tie__**s** adjust BC/BCa confidence intervals for ties
* **mse** use MSE formula for variance estimation

Reporting
__l__**evel(***#***)** set confidence level; default is **level(95)**
**n(***#***)** *#* of observations from which bootstrap samples were
taken
**notable** suppress table of results
__noh__**eader** suppress table header
__nol__**egend** suppress table legend
__v__**erbose** display the full table legend
__ti__**tle(***text***)** use *text* as title for bootstrap results
*display_options* control column formats and line width
-------------------------------------------------------------------------
* Starred options and qualifiers **using**, **if**, and **in** require a bootstrap
dataset.
See **[R] bootstrap postestimation** for features available after estimation.

__Menu__

**Statistics > Resampling > Report bootstrap results**

__Description__

**bstat** is a programmer's command that computes and displays estimation
results from bootstrap statistics. For each variable in *varlist*, **bstat**
computes a covariance matrix, estimates bias, and constructs normal
confidence intervals (CIs), percentile CIs, bias-corrected (BC) CIs, and
bias-corrected and accelerated (BCa) CIs using a bootstrap dataset in
memory or on disk. The computed CIs can be displayed using **estat**
**bootstrap**; see **[R] bootstrap postestimation**.

**bstat** without *varlist* replays results from the last bootstrap estimation
when results are stored in **e()**.

__Options__

+------+
----+ Main +-------------------------------------------------------------

**stat(***vector***)** specifies the observed value of each statistic (that is, the
value of the statistic using the original dataset).

**accel(***vector***)** specifies the acceleration of each statistic, which is used
to construct BCa CIs.

**ties** specifies that **bstat** adjust for ties in the replicate values when
computing the median bias used to construct BC and BCa CIs.

**mse** specifies that **bstat** compute the variance by using deviations of the
replicates from the observed value of the statistics. By default,
**bstat** computes the variance by using deviations from the average of
the replicates.

+-----------+
----+ Reporting +--------------------------------------------------------

**level(***#***)**; see **[R] estimation options**.

**n(***#***)** specifies the number of observations from which bootstrap samples
were taken. This value is used in no calculations but improves the
table header when this information is not saved in the bootstrap
dataset.

**notable** suppresses the display of the output table.

**noheader** suppresses the display of the table header. This option implies
**nolegend**.

**nolegend** suppresses the display of the table legend.

**verbose** specifies that the full table legend be displayed. By default,
coefficients and standard errors are not displayed.

**title(***text***)** specifies a title to be displayed above the table of
bootstrap results; the default title is **Bootstrap results**.

*display_options*: **cformat(***%fmt***)**, **pformat(%***fmt***)**, **sformat(%***fmt***)**, and
**nolstretch**; see **[R] estimation options**.

__Example__

Setup
**. sysuse auto**
**. bootstrap _b, saving(bstat) reps(200) bca:** **regress mpg weight**
**length**

Save the acceleration statistic vector
**. matrix a = e(accel)**

Save the estimated coefficients from the full sample
**. matrix b = e(b)**

Replay the bootstrap results by using the saved full sample estimate
vector and the saved acceleration vector
**. bstat using bstat, stat(b) accel(a)**

__Stored results__

**bstat** stores 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_strata)** number of strata
**e(N_clust)** number of clusters
**e(k_aux)** number of auxiliary parameters
**e(k_eq)** number of equations in **e(b)**
**e(k_exp)** number of standard expressions
**e(k_eexp)** number of extended expressions (i.e., **_b**)
**e(k_extra)** number of extra equations beyond the original
ones from **e(b)**
**e(level)** confidence level for bootstrap CIs
**e(bs_version)** version for **bootstrap** results
**e(rank)** rank of **e(V)**

Macros
**e(cmd)** **bstat**
**e(command)** from **_dta[command]**
**e(cmdline)** command as typed
**e(title)** title in estimation output
**e(exp***#***)** expression for the *#*th statistic
**e(prefix)** **bootstrap**
**e(ties)** **ties**, if specified
**e(mse)** **mse**, if specified
**e(vce)** **bootstrap**
**e(vcetype)** title used to label Std. Err.
**e(properties)** **b V**

Matrices
**e(b)** observed statistics
**e(b_bs)** bootstrap estimates
**e(reps)** number of nonmissing results
**e(bias)** estimated biases
**e(se)** estimated standard errors
**e(z0)** median biases
**e(accel)** estimated accelerations
**e(ci_normal)** normal-approximation CIs
**e(ci_percentile)** percentile CIs
**e(ci_bc)** bias-corrected CIs
**e(ci_bca)** bias-corrected and accelerated CIs
**e(V)** bootstrap variance-covariance matrix