help scobit dialogs: scobit svy: scobit
also see: scobit postestimation
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Title
[R] scobit -- Skewed logistic regression
Syntax
scobit depvar [indepvars] [if] [in] [weight] [, options]
options description
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Model
noconstant suppress constant term
offset(varname) include varname in model with coefficient
constrained to 1
asis retain perfect predictor variables
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)
or report odds 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
+ 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.
bootstrap, by, jackknife, nestreg, rolling, statsby, stepwise, and svy
are allowed; see 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] scobit postestimation for features available after estimation.
Menu
Statistics > Binary outcomes > Skewed logit regression
Description
scobit fits a maximum-likelihood skewed logit model.
See logistic estimation commands for a list of related estimation
commands.
Options
+-------+
----+ Model +------------------------------------------------------------
noconstant, offset(varname), constraint(constraints), collinear; see [R]
estimation options.
asis forces retention of perfect predictor variables and their associated
perfectly predicted observations and may produce instabilities in
maximization; see [R] probit.
+-----------+
----+ 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.
or reports the estimated coefficients transformed to odds ratios, i.e.,
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 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.
Setting the optimization type to technique(bhhh) resets the default
vcetype to vce(opg).
The following option is available with scobit but is not shown in the
dialog box:
coeflegend; see [R] estimation options.
Example
. sysuse auto
. scobit foreign mpg
. scobit foreign mpg, vce(robust)
Saved results
scobit saves the following in e():
Scalars
e(N) number of observations
e(k) number of parameters
e(k_eq) number of equations
e(k_aux) number of auxiliary parameters
e(k_dv) number of dependent variables
e(k_autoCns) number of base, empty, and omitted constraints
e(ll) log likelihood
e(ll_c) log likelihood, comparison model
e(N_f) number of failures (zero outcomes)
e(N_s) number of successes (nonzero outcomes)
e(alpha) alpha
e(N_clust) number of clusters
e(chi2) chi-squared
e(chi2_c) chi-squared for comparison test
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) scobit
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(chi2_ct) Wald or LR; type of model chi-squared test
corresponding to e(chi2_c)
e(vce) vcetype specified in vce()
e(vcetype) title used to label Std. Err.
e(diparm#) display transformed parameter #
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(predict) program used to implement predict
e(footnote) program used to implement the footnote display
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] scobit
Help: [R] scobit postestimation;
[R] cloglog, [R] glm, [R] logistic
