help vwls dialog: vwls
also see: vwls postestimation
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Title
[R] vwls -- Variance-weighted least squares
Syntax
vwls depvar indepvars [if] [in] [weight] [, options]
options description
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Model
noconstant suppress constant term
sd(varname) variable containing estimate of conditional standard
deviation
Reporting
level(#) set confidence level; default is level(95)
display_options control spacing and display of omitted variables and
base and empty cells
+ 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, rolling, and statsby are allowed; see prefix.
Weights are not allowed with the bootstrap prefix.
fweights are allowed; see weight.
See [R] vwls postestimation for features available after estimation.
Menu
Statistics > Linear models and related > Other > Variance-weighted least
squares
Description
vwls estimates a linear regression using variance-weighted least squares.
It differs from ordinary least-squares (OLS) regression in that it does
not assume homogeneity of variance, but requires that the conditional
variance of depvar be estimated prior to the regression. The estimated
variance need not be constant across observations. vwls treats the
estimated variance as if it were the true variance when it computes
standard errors of the coefficients.
You must supply an estimate of the conditional standard deviation of
depvar to vwls by using the sd(varname) option, or you must have grouped
data with groups defined by the indepvars variables. In the latter case,
vwls treats all indepvars as categorical variables, computes the mean and
standard deviation of depvar separately for each subgroup, and computes
the regression of the subgroup means on indepvars.
Options
+-------+
----+ Model +------------------------------------------------------------
noconstant; see [R] estimation options.
sd(varname) specifies an estimate of the conditional standard deviation
of depvar (that is, it can vary observation by observation). All
values of varname must be > 0. If you specify sd(), you cannot use
fweights.
If sd() is not given, the data will be grouped by indepvars. Here
indepvars are treated as categorical variables, and the means and
standard deviations of depvars for each subgroup are calculated and
used for the regression. Any subgroup for which the standard
deviation is zero is dropped.
+-----------+
----+ Reporting +--------------------------------------------------------
level(#); see [R] estimation options.
display_options: noomitted, vsquish, noemptycells, baselevels,
allbaselevels; see [R] estimation options.
The following option is available with vwls but is not shown in the
dialog box:
coeflegend; see [R] estimation options.
Example
. webuse bp
. vwls bp gender race
Saved results
vwls saves the following in e():
Scalars
e(N) number of observations
e(df_m) model degrees of freedom
e(chi2) model chi-squared
e(df_gf) goodness-of-fit degrees of freedom
e(chi2_gf) goodness-of-fit chi-squared
e(rank) rank of e(V)
Macros
e(cmd) vwls
e(cmdline) command as typed
e(depvar) name of dependent variable
e(properties) b V
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(V) variance-covariance matrix of the estimators
Functions
e(sample) marks estimation sample
Also see
Manual: [R] vwls
Help: [R] vwls postestimation;
[R] regress
