Stata 15 help for weight

Title

[U] 11.1.6 weight -- Weights

Remarks

Most Stata commands can deal with weighted data. Stata allows four kinds of weights:

1. fweights, or frequency weights, are weights that indicate the number of duplicated observations.

2. pweights, or sampling weights, are weights that denote the inverse of the probability that the observation is included because of the sampling design.

3. aweights, or analytic weights, are weights that are inversely proportional to the variance of an observation; that is, the variance of the jth observation is assumed to be sigma^2/w_j, where w_j are the weights. Typically, the observations represent averages and the weights are the number of elements that gave rise to the average. For most Stata commands, the recorded scale of aweights is irrelevant; Stata internally rescales them to sum to N, the number of observations in your data, when it uses them.

4. iweights, or importance weights, are weights that indicate the "importance" of the observation in some vague sense. iweights have no formal statistical definition; any command that supports iweights will define exactly how they are treated. Usually, they are intended for use by programmers who want to produce a certain computation.

The general syntax is

command ... [weightword=exp] ...

For example:

. anova y x1 x2 x1*x2 [fweight=pop]

. regress avgy avgx1 avgx2 [aweight=cellpop]

. regress y x1 x2 x3 [pweight=1/prob]

. scatter y x [aweight=y2], mfcolor(none)

You type the square brackets.

Stata allows abbreviations: fw for fweight, aw for aweight, and so on. You could type

. anova y x1 x2 x1*x2 [fw=pop]

. regress avgy avgx1 avgx2 [aw=cellpop]

. regress y x1 x2 x3 [pw=1/prob]

. scatter y x [aw=y2], mfcolor(none)

Also, each command has its own idea of the "natural" kind of weight. If you type

. regress avgy avgx1 avgx2 [w=cellpop]

the command will tell you what kind of weight it is assuming and perform the request as if you specified that kind of weight.

There are synonyms for some of the weight types. fweight can also be referred to as frequency (abbreviation freq). aweight can be referred to as cellsize (abbreviation cell):

. anova y x1 x2 x1*x2 [freq=pop]

. regress avgy avgx1 avgx2 [cell=cellpop]

fweights

Frequency fweights indicate replicated data. The weight tells the command how many observations each observation really represents. fweights allow data to be stored more parsimoniously. The weighting variable contains positive integers. The result of the command is the same as if you duplicated each observation however many times and then ran the command unweighted.

pweights

Sampling pweights indicate the inverse of the probability that this observation was sampled. Commands that allow pweights typically provide a vce(cluster clustvar) option. These can be combined to produce estimates for unstratified cluster-sampled data. If you must also deal with issues of stratification, see [SVY] survey.

aweights

Analytic aweights are typically appropriate when you are dealing with data containing averages. For instance, you have average income and average characteristics on a group of people. The weighting variable contains the number of persons over which the average was calculated (or a number proportional to that amount).

iweights

This weight has no formal statistical definition and is a catch-all category. The weight somehow reflects the importance of the observation and any command that supports such weights will define exactly how such weights are treated.

Examples

. webuse hanley The next four commands are equivalent . roctab disease rating [fweight=pop] . roctab disease rating [fw=pop] . roctab disease rating [freq=pop] . roctab disease rating [weight=pop]

. webuse total . total heartatk [pw=swgt], over(sex)

. webuse byssin . anova prob workplace smokes race workplace#smokes [aw=pop]

. webuse nhanes2f . svyset psuid [pw=finalwgt], strata(stratid) . svy: ologit health female black age c.age#c.age . ologit health female black age c.age#c.age [iw=finalwgt]


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