[U] User's Guide

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24 [ U ] 1 Read this—it will helplinearized variance estimator of the response that accounts for the sampling distribution of thecovariates. Thus inferences can be made about the population. See [R] margins.2. Survey estimators may be used with Stata’s new multiple-imputation features. Either svyset yourdata before you mi set your data or use mi svyset afterward. See [MI] intro.3. Survey commands now report population and subpopulation sizes with a larger number of digits,reserving scientific notation only for sizes greater than 99 trillion.4. Survey estimation commands may now be used with factor variables; see [U] 11.4.3 Factorvariables.5. New reporting options baselevels and allbaselevels control how base levels of factor variablesare displayed in output tables. New reporting option noemptycells controls whether missing cellsin interactions are displayed. These new options are supported by existing prefix command svy andexisting postestimation commands estat effects and estat vce. See [R] estimation options.6. New reporting option noomitted controls whether covariates that are dropped because of collinearityare reported in output tables. By default, Stata now includes a line in estimation and related outputtables for collinear covariates and marks those covariates as “(omitted)”. noomitted suppressesthose lines.noomitted is supported by prefix command svy and postestimation commands estat effectsand estat vce. See [R] estimation options.7. New option vsquish eliminates blank lines in estimation and related tables. Many output tablesnow set off factor variables and time-series–operated variables with a blank line. vsquish removesthese lines.vsquish is supported by prefix command svy and postestimation command estat effects.8. Prefix command svy now supports new option coeflegend to display the coefficients’ legend ratherthan the coefficient table. The legend shows how you would type a coefficient in an expression,in a test command, or in a constraint definition. See [R] estimation options.9. Prefix command svy now supports new option nocnsreport to suppress reporting constraints;see [R] estimation options.1.3.9 What’s new in statistics (multiple imputation)1. All of it. Multiple imputation is about the analysis of data for which some values are missing.See [MI] intro.2. New command misstable makes tables that help you understand the pattern of missing valuesin your data; see [R] misstable and [MI] mi misstable.3. Estimation commands that may be used with mi estimate include the following:
[ U ] 1.3 What’s new 25command entry descriptionLinear regression modelsregress [R] regress Linear regressioncnsreg [R] cnsreg Constrained linear regressionmvreg [R] mvreg Multivariate regressionBinary-response regression modelslogistic [R] logistic Logistic regression, reporting odds ratioslogit [R] logit Logistic regression, reporting coefficientsprobit [R] probit Probit regressioncloglog [R] cloglog Complementary log-log regressionbinreg [R] binreg GLM for the binomial familyCount-response regression modelspoisson [R] poisson Poisson regressionnbreg [R] nbreg Negative binomial regressiongnbreg [R] nbreg Generalized negative binomial regressionOrdinal-response regression modelsologit [R] ologit Ordered logistic regressionoprobit [R] oprobit Ordered probit regressionCategorical-response regression modelsmlogit [R] mlogit Multinomial (polytomous) logistic regressionmprobit [R] mprobit Multinomial probit regressionclogit [R] clogit Conditional (fixed-effects) logistic regressionQuantile regression modelsqreg [R] qreg Quantile regressioniqreg [R] qreg Interquantile range regressionsqreg [R] qreg Simultaneous-quantile regressionbsqreg [R] qreg Quantile regression with bootstrap standard errorsSurvival regression modelsstcox [ST] stcox Cox proportional hazards modelstreg [ST] streg Parametric survival modelsstcrreg [ST] stcrreg Competing-risks regressionOther regression modelsglm [R] glm Generalized linear modelsareg [R] areg Linear regression with a large dummy-variable setrreg [R] rreg Robust regressiontruncreg [R] truncreg Truncated regressionDescriptive statisticsmean [R] mean Estimate meansproportion [R] proportion Estimate proportionsratio [R] ratio Estimate ratiosSurvey regression modelssvy: [SVY] svy Estimation commands for survey data (excluding commandsthat are not listed above)
Page 1 and 2: A Stata Press PublicationStataCorp
Page 3 and 4: iTable of contentsStata basics1 Rea
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Page 48 and 49: 36 [ U ] 2 A brief description of S
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76 [ U ] 9 The Break key9.2 Side ef
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78 [ U ] 10 Keyboard usesave is the
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80 [ U ] 10 Keyboard use10.4 Editin
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82 [ U ] 10 Keyboard useAnother met
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11 Language syntaxContents11.1 Over
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[ U ] 11.1 Overview 8711.1.2 by var
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[ U ] 11.1 Overview 89. summarize m
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[ U ] 11.1 Overview 91Example 7Nega
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11.1.7 options[ U ] 11.1 Overview 9
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[ U ] 11.1 Overview 9511.1.8 numlis
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[ U ] 11.2 Abbreviation rules 97by
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[ U ] 11.3 Naming conventions 99The
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[ U ] 11.4 varlists 101You may use
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[ U ] 11.4 varlists 103Consider a v
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[ U ] 11.4 varlists 105Here are som
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[ U ] 11.4 varlists 107You can sele
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[ U ] 11.4 varlists 109. use http:/
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[ U ] 11.5 by varlist: construct 11
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[ U ] 11.5 by varlist: construct 11
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[ U ] 11.6 File-naming conventions
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12 DataContents12.1 Data and datase
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[ U ] 12.2 Numbers 119. display 2/0
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[ U ] 12.2 Numbers 121Technical not
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[ U ] 12.4 Strings 12312.4 StringsA
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[ U ] 12.5 Formats: Controlling how
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[ U ] 12.6 Dataset, variable, and v
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[ U ] 12.8 Characteristics 139You c
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[ U ] 12.10 References 141The Varia
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144 [ U ] 13 Functions and expressi
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162 [ U ] 14 Matrix expressionsHere
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164 [ U ] 14 Matrix expressionsWe c
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166 [ U ] 14 Matrix expressions. ma
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168 [ U ] 14 Matrix expressionsRega
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170 [ U ] 14 Matrix expressionsEith
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172 [ U ] 14 Matrix expressionsThe
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174 [ U ] 14 Matrix expressions7. W
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176 [ U ] 15 Saving and printing ou
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182 [ U ] 16 Do-filesYou then enter
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184 [ U ] 16 Do-files* a sample ana
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186 [ U ] 16 Do-files16.1.4 Error h
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188 [ U ] 16 Do-filesMany users inc
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190 [ U ] 16 Do-files5. If Stata is
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192 [ U ] 16 Do-filesyou could writ
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17 Ado-filesContents17.1 Descriptio
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[ U ] 17.5 Where does Stata look fo
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17.6 How do I install an addition?A
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18 Programming StataContents18.1 De
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[ U ] 18.2 Relationship between a p
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[ U ] 18.3 Macros 205That problem i
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[ U ] 18.3 Macros 207For the right
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[ U ] 18.3 Macros 209To a programme
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[ U ] 18.3 Macros 211Because Stata
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[ U ] 18.3 Macros 213Above we have
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[ U ] 18.3 Macros 21518.3.10 Advanc
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[ U ] 18.4 Program arguments 217You
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[ U ] 18.4 Program arguments 219Let
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[ U ] 18.4 Program arguments 221Equ
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[ U ] 18.4 Program arguments 223pro
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[ U ] 18.4 Program arguments 22518.
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[ U ] 18.7 Temporary objects 22718.
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[ U ] 18.8 Accessing results calcul
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[ U ] 18.9 Accessing results calcul
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[ U ] 18.10 Saving results 2333. Co
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[ U ] 18.10 Saving results 2355. Yo
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[ U ] 18.11 Ado-files 237e(sample)
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[ U ] 18.11 Ado-files 239If you wri
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[ U ] 18.11 Ado-files 241duck is co
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[ U ] 18.11 Ado-files 243begin fvar
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[ U ] 18.11 Ado-files 245begin fvar
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Technical note[ U ] 18.11 Ado-files
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[ U ] 18.11 Ado-files 249{phang}{op
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[ U ] 18.11 Ado-files 2515. Include
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[ U ] 18.13 References 253Technical
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256 [ U ] 19 Immediate commands19.1
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258 [ U ] 19 Immediate commands19.1
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260 [ U ] 20 Estimation and postest
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316 [ U ] 21 Inputting data21.2 Det
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318 [ U ] 21 Inputting dataM,Joe Sm
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320 [ U ] 21 Inputting dataTechnica
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322 [ U ] 21 Inputting dataAnother
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22 Combining datasetsYou have two d
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23 Working with stringsContents23.1
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[ U ] 23.4 Complex strings 329The p
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24 Working with dates and timesCont
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[ U ] 24.2 Inputting dates and time
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[ U ] 24.2 Inputting dates and time
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[ U ] 24.6 Converting between date
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25 Working with categorical data an
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[ U ] 25.1 Continuous, categorical,
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[ U ] 25.2 Estimation with factor v
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26 Overview of Stata estimation com
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[ U ] 26.3 ANOVA, ANCOVA, MANOVA, a
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[ U ] 26.5 Binary-outcome qualitati
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[ U ] 26.9 Exact estimators 363In t
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[ U ] 26.14 Models with time-series
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[ U ] 26.15 Panel-data models 367xt
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26.15.6 Random-coefficient models w
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[ U ] 26.21 Multivariate and cluste
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[ U ] 26.25 Reference 373should try
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376 [ U ] 27 Commands everyone shou
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378 [ U ] 28 Using the Internet to
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390 Subject and author indexcoeffic
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392 Subject and author indexIif exp
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394 Subject and author indexPiantad
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396 Subject and author indexUnix,ke
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