help poisson dialogs: poisson svy: poisson
also see: poisson postestimation
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Title
[R] poisson -- Poisson regression
Syntax
poisson depvar [indepvars] [if] [in] [weight] [, options]
options description
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Model
noconstant suppress constant term
exposure(varname_e) include ln(varname_e) in model with
coefficient constrained to 1
offset(varname_o) include varname_o in model with coefficient
constrained to 1
constraints(constraints) apply specified linear constraints
collinear keep collinear variables
SE/Robust
vce(vcetype) vcetype may be oim, robust, cluster
clustvar, opg, bootstrap, or jackknife
Reporting
level(#) set confidence level; default is level(95)
irr report incidence-rate ratios
nocnsreport do not display constraints
display_options control spacing and display of omitted
variables and base and empty cells
Maximization
maximize_options control the maximization process; seldom
used
+ coeflegend display coefficients' legend instead of
coefficient table
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+ coeflegend does not appear in the dialog box.
indepvars may contain factor variables; see fvvarlist.
depvar, indepvars, varname_e, and varname_o may contain time-series
operators; see tsvarlist.
bootstrap, by, fracpoly, jackknife, mfp, mi estimate, nestreg, rolling,
statsby, stepwise, svy are allowed; see prefix.
vce(bootstrap) and vce(jackknife) are not allowed with the mi estimate
prefix.
Weights are not allowed with the bootstrap prefix.
vce() and weights are not allowed with the svy prefix.
fweights, iweights, and pweights are allowed; see weight.
See [R] poisson postestimation for features available after estimation.
Menu
Statistics > Count outcomes > Poisson regression
Description
poisson fits a Poisson regression of depvar on indepvars, where depvar is
a nonnegative count variable.
If you have panel data, see [XT] xtpoisson.
Options
+-------+
----+ Model +------------------------------------------------------------
noconstant, exposure(varname_e), offset(varname_o),
constraints(constraints), collinear; see [R] estimation options.
+-----------+
----+ SE/Robust +--------------------------------------------------------
vce(vcetype) specifies the type of standard error reported, which
includes types that are derived from asymptotic theory, that are
robust to some kinds of misspecification, that allow for intragroup
correlation, and that use bootstrap or jackknife methods; see [R]
vce_option.
+-----------+
----+ Reporting +--------------------------------------------------------
level(#); see [R] estimation options.
irr reports estimated coefficients transformed to incidence-rate ratios,
that is, exp(b) rather than b. Standard errors and confidence
intervals are similarly transformed. This option affects how results
are displayed, not how they are estimated or stored. irr may be
specified at estimation or when replaying previously estimated
results.
nocnsreport; see [R] estimation options.
display_options: noomitted, vsquish, noemptycells, baselevels,
allbaselevels; see [R] estimation options.
+--------------+
----+ Maximization +-----------------------------------------------------
maximize_options: difficult, technique(algorithm_spec), iterate(#),
[no]log, trace, gradient, showstep, hessian, showtolerance,
tolerance(#), ltolerance(#), nrtolerance(#), nonrtolerance,
from(init_specs); see [R] maximize. These options are seldom used.
Setting the optimization type to technique(bhhh) resets the default
vcetype to vce(opg).
The following option is available with poisson but is not shown in the
dialog box:
coeflegend; see [R] estimation options.
Examples
Setup
. webuse dollhill3
Fit a Poisson regression
. poisson deaths smokes i.agecat, exposure(pyears)
Obtain incidence-rate ratios
. poisson deaths smokes i.agecat, exposure(pyears) irr
Redisplay results, but with 99% confidence intervals
. poisson, level(99) irr
Saved results
poisson saves the following in e():
Scalars
e(N) number of observations
e(k) number of parameters
e(k_eq) number of equations
e(k_eq_model) number of equations in model Wald test
e(k_dv) number of dependent variables
e(k_autoCns) number of base, empty, and omitted constraints
e(df_m) model degrees of freedom
e(r2_p) pseudo-R-squared
e(ll) log likelihood
e(ll_0) log likelihood, constant-only model
e(N_clust) number of clusters
e(chi2) chi-squared
e(p) significance
e(rank) rank of e(V)
e(ic) number of iterations
e(rc) return code
e(converged) 1 if converged, 0 otherwise
Macros
e(cmd) poisson
e(cmdline) command as typed
e(depvar) name of dependent variable
e(wtype) weight type
e(wexp) weight expression
e(title) title in estimation output
e(clustvar) name of cluster variable
e(offset) offset
e(chi2type) Wald or LR; type of model chi-squared test
e(vce) vcetype specified in vce()
e(vcetype) title used to label Std. Err.
e(opt) type of optimization
e(which) max or min; whether optimizer is to perform
maximization or minimization
e(ml_method) type of ml method
e(user) name of likelihood-evaluator program
e(technique) maximization technique
e(singularHmethod) m-marquardt or hybrid; method used when Hessian is
singular
e(crittype) optimization criterion
e(properties) b V
e(estat_cmd) program used to implement estat
e(predict) program used to implement predict
e(asbalanced) factor variables fvset as asbalanced
e(asobserved) factor variables fvset as asobserved
Matrices
e(b) coefficient vector
e(Cns) constraints matrix
e(ilog) iteration log (up to 20 iterations)
e(gradient) gradient vector
e(V) variance-covariance matrix of the estimators
e(V_modelbased) model-based variance
Functions
e(sample) marks estimation sample
Also see
Manual: [R] poisson
Help: [R] poisson postestimation;
[R] glm, [R] nbreg, [SVY] svy estimation, [XT] xtpoisson, [R]
zip, [R] ztp
