[SVY] Survey Data

1 STATA Survey DATA REFERENCEMANUALRELEASE 13 A Stata Press PublicationStataCorp LPCollege Station, Texas Copyrightc 1985 2013 StataCorp LPAll rights reservedVersion 13 Published by Stata Press, 4905 Lakeway Drive, College Station, Texas 77845 Typeset in TEXISBN-10: 1-59718-125-0 ISBN-13: 978-1-59718-125-9 This manual is protected by copyright. All rights are reserved. No part of this manual may be reproduced, storedin a retrieval system, or transcribed, in any form or by any means electronic, mechanical, photocopy, recording, orotherwise without the prior written permission of StataCorp LP unless permitted subject to the terms and conditionsof a license granted to you by StataCorp LP to use the software and documentation. No license, express or implied,by estoppel or otherwise, to any intellectual property rights is granted by this provides this manual as is without warranty of any kind, either expressed or implied, including, butnot limited to, the implied warranties of merchantability and fitness for a particular purpose.

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3 : Release 13. Statistical Software. College Station, TX: StataCorp .. Introduction to Survey data manual1survey .. Introduction to Survey commands2bootstrapoptions.. More options for bootstrap variance estimation24brroptions.. More options forBRRvariance estimation25direct standardization .. Direct standardization of means, proportions, and ratios27estat .. Postestimation statistics for Survey data31jackknifeoptions.. More options for jackknife variance estimation51ml for svy .. Maximum pseudolikelihood estimation for Survey data52poststratification .. Poststratification for Survey data54sdroptions.. More options forSDRvariance estimation58subpopulation estimation .. Subpopulation estimation for Survey data59svy .. The Survey prefix command65svy bootstrap .. Bootstrap for Survey data73svy brr .. Balanced repeated replication for Survey data81svy estimation.

4 Estimation commands for Survey data89svy jackknife .. Jackknife estimation for Survey data 101svy postestimation .. Postestimation tools for svy 109svy sdr .. Successive difference replication for Survey data 126svy: tabulate oneway .. One-way tables for Survey data 132svy: tabulate twoway .. Two-way tables for Survey data 138svydescribe .. Describe Survey data 158svymarkout .. Mark observations for exclusion on the basis of Survey characteristics 164svyset .. Declare Survey design for dataset 165variance estimation .. Variance estimation for Survey data 182iii ContentsGlossary ..197 Subject and author index ..201 Cross-referencing the documentationWhen reading this manual, you will find references to other Stata manuals. For example,[U] 26 Overview of Stata estimation commands[R]regress[D]reshapeThe first example is a reference to chapter 26,Overview of Stata estimation commands, in theUser sGuide; the second is a reference to theregressentry in theBase Reference Manual.

5 And the thirdis a reference to thereshapeentry in theData Management Reference the manuals in the Stata Documentation have a shorthand notation:[GSM]Getting Started with Stata for Mac[GSU]Getting Started with Stata for Unix[GSW]Getting Started with Stata for Windows[U]Stata User s Guide[R]Stata Base Reference Manual[D]Stata Data Management Reference Manual[G]Stata Graphics Reference Manual[XT]Stata Longitudinal-Data/Panel-Data Reference Manual[ME]Stata Multilevel Mixed-Effects Reference Manual[MI]Stata Multiple-Imputation Reference Manual[MV]Stata multivariate Statistics Reference Manual[PSS]Stata Power and Sample-Size Reference Manual[P]Stata Programming Reference Manual[SEM]Stata Structural Equation Modeling Reference Manual [SVY] Stata Survey Data Reference Manual[ST]Stata Survival Analysis and Epidemiological Tables Reference Manual[TS]Stata Time-Series Reference Manual[TE]Stata Treatment-Effects Reference Manual.

6 Potential Outcomes/Counterfactual Outcomes[I]Stata Glossary and Index[M]Mata Reference ManualiiiTitleintro Introduction to Survey data manualDescriptionRemarks and examplesAlso seeDescriptionThis entry describes this manual and what has changed since Stata 12. See the next entry,[SVY] Survey , for an introduction to Stata s Survey and examplesThis manual documents the Survey data commands and is referred to as [SVY] in this entry, [SVY]surveyprovides an overview of the Survey commands. This manual isarranged alphabetically. If you are new to Stata s Survey data commands, we recommend that youread the following sections first:[SVY]surveyIntroduction to Survey commands [SVY] svysetDeclare Survey design for dataset [SVY] svydescribeDescribe Survey data [SVY] svy estimationEstimation commands for Survey data [SVY] svy postestimationPostestimation tools for svyStata is continually being updated, and Stata users are continually writing new commands.

7 Tofind out about the latest Survey data features, typesearch surveyafter installing the latest officialupdates; see [R] s newFor a complete list of all the new features in Stata 13, see[U] What s see[U] What s new[R]intro Introduction to base reference manual1 Titlesurvey Introduction to Survey commandsDescriptionRemarks and examplesAcknowledgmentsReferencesAlso seeDescriptionTheSurvey Data Reference Manualis organized alphabetically, making it easy to find an individualentry if you know the name of a command. This overview organizes and presents the commandsconceptually, that is, according to the similarities in the functions they design tools [SVY] svysetDeclare Survey design for dataset [SVY] svydescribeDescribe Survey dataSurvey data analysis tools [SVY] svyThe Survey prefix command [SVY] svy estimationEstimation commands for Survey data [SVY] svy: tabulate onewayOne-way tables for Survey data [SVY] svy.

8 Tabulate twowayTwo-way tables for Survey data [SVY] svy postestimationPostestimation tools for svy [SVY] estatPostestimation statistics for Survey data, such as design effects [SVY] svy bootstrapBootstrap for Survey data [SVY] bootstrapoptionsMore options for bootstrap variance estimation [SVY] svy brrBalanced repeated replication for Survey data [SVY] brroptionsMore options forBRRvariance estimation [SVY] svy jackknifeJackknife estimation for Survey data [SVY] jackknifeoptionsMore options for jackknife variance estimation [SVY] svy sdrSuccessive difference replication for Survey data [SVY] sdroptionsMore options forSDRvariance estimationSurvey data concepts [SVY] variance estimationVariance estimation for Survey data [SVY] subpopulation estimationSubpopulation estimation for Survey data [SVY] direct standardizationDirect standardization of means, proportions, and ratios [SVY] poststratificationPoststratif ication for Survey dataTools for programmers of new Survey commands [SVY] ml for svyMaximum pseudolikelihood estimation for Survey data [SVY] svymarkoutMark observations for exclusion on the basis of surveycharacteristics2survey Introduction to Survey commands 3 Remarks and examplesRemarks are presented under the following headings:IntroductionSurvey design toolsSurvey data analysis toolsSurvey data conceptsTools for programmers of new Survey commandsVideo exampleIntroductionStata s facilities for Survey data analysis are centered around thesvyprefix command.

9 After youidentify the Survey design characteristics with thesvysetcommand, prefix the estimation commandsin your data analysis with svy: . For example, where you would normally use theregresscommandto fit a linear regression model for nonsurvey data, usesvy: regressto fit a linear regression modelfor your Survey should you use thesvyprefix command when you have Survey data? To answer this question,we need to discuss some of the characteristics of Survey design and Survey data collection becausethese characteristics affect how we must perform our analysis if we want to get it data are characterized by the following: Sampling weights, also called probability weights pweights in Stata s terminology Cluster sampling StratificationThese features arise from the design and details of the data collection procedure. Here s a briefdescription of how these design features affect the analysis of the data: Sampling weights.

10 In sample surveys, observations are selected through a random process,but different observations may have different probabilities of selection. Weights are equal to(or proportional to) the inverse of the probability of being sampled. Various postsamplingadjustments to the weights are sometimes made, as well. A weight ofwjfor thejth observationmeans, roughly speaking, that thejth observation representswjelements in the populationfrom which the sample was weights from the analysis results in estimates that may be biased, sometimes seriouslyso. Sampling weights also play a role in estimating standard errors. Clustering. Individuals are not sampled independently in most Survey designs. Collections ofindividuals (for example, counties, city blocks, or households) are typically sampled as a group,known as may also be further subsampling within the clusters.