[R] Base Reference Stata Manual V13
User Manual:
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- Contents
- [IG] Installation Guide
- Simple installation
- Installing Stata for Windows
- Installing Stata for Mac
- Installing Stata for Unix
- Installation overview
- Find your installation DVD and paper license
- Obtain superuser access
- Create a directory for Stata
- Upgrading
- Install Stata
- Initialize the license
- Set the message of the day (optional)
- Verify that Stata is working
- Modify shell start-up script
- Update Stata if necessary
- Starting Stata
- Exiting Stata
- Troubleshooting Unix installation
- Troubleshooting Unix start-up
- Stata(console) starts but Stata(GUI) does not
- Platforms and flavors
- Documentation
- [GS] Getting Started
- [GSM] Mac
- Contents
- 1 Introducing Stata---sample session
- 2 The Stata user interface
- 3 Using the Viewer
- The Viewer's purpose
- Viewer buttons
- Viewer's function
- Viewing local text files, including SMCL files
- Viewing remote files over the Internet
- Navigating within the Viewer
- Printing
- Tabs in the Viewer
- Right-clicking on the Viewer window
- Searching for help in the Viewer
- Commands in the Viewer
- Using the Viewer from the Command window
- 4 Getting help
- 5 Opening and saving Stata datasets
- 6 Using the Data Editor
- 7 Using the Variables Manager
- 8 Importing data
- 9 Labeling data
- 10 Listing data and basic command syntax
- 11 Creating new variables
- 12 Deleting variables and observations
- 13 Using the Do-file Editor---automating Stata
- 14 Graphing data
- 15 Editing graphs
- 16 Saving and printing results by using logs
- 17 Setting font and window preferences
- 18 Learning more about Stata
- 19 Updating and extending Stata---Internet functionality
- A Troubleshooting Stata
- B Advanced Stata usage
- C More on Stata for Mac
- Subject index
- [GSU] Unix
- Contents
- 1 Introducing Stata---sample session
- 2 The Stata user interface
- 3 Using the Viewer
- The Viewer in Stata(GUI)
- The Viewer's purpose
- Viewer buttons
- Viewer's function
- Viewing local text files, including SMCL files
- Viewing remote files over the Internet
- Navigating within the Viewer
- Printing
- Tabs in the Viewer
- Right-clicking on the Viewer window
- Searching for help in the Viewer
- Commands in the Viewer
- Using the Viewer from the Command window
- 4 Getting help
- 5 Opening and saving Stata datasets
- 6 Using the Data Editor
- 7 Using the Variables Manager
- 8 Importing data
- 9 Labeling data
- 10 Listing data and basic command syntax
- 11 Creating new variables
- 12 Deleting variables and observations
- 13 Using the Do-file Editor---automating Stata
- 14 Graphing data
- 15 Editing graphs
- 16 Saving and printing results by using logs
- 17 Setting font and window preferences
- 18 Learning more about Stata
- 19 Updating and extending Stata---Internet functionality
- A Troubleshooting Stata
- B Advanced Stata usage
- C Stata manual pages for Unix
- conren
- stata
- Subject index
- [GSW] Windows
- Contents
- 1 Introducing Stata---sample session
- 2 The Stata user interface
- 3 Using the Viewer
- The Viewer's purpose
- Viewer buttons
- Viewer's function
- Viewing local text files, including SMCL files
- Viewing remote files over the Internet
- Navigating within the Viewer
- Printing
- Tabs in the Viewer
- Right-clicking on the Viewer window
- Searching for help in the Viewer
- Commands in the Viewer
- Using the Viewer from the Command window
- 4 Getting help
- 5 Opening and saving Stata datasets
- 6 Using the Data Editor
- 7 Using the Variables Manager
- 8 Importing data
- 9 Labeling data
- 10 Listing data and basic command syntax
- 11 Creating new variables
- 12 Deleting variables and observations
- 13 Using the Do-file Editor---automating Stata
- 14 Graphing data
- 15 Editing graphs
- 16 Saving and printing results by using logs
- 17 Setting font and window preferences
- 18 Learning more about Stata
- 19 Updating and extending Stata---Internet functionality
- A Troubleshooting Stata
- B Advanced Stata usage
- C More on Stata for Windows
- Subject index
- [GSM] Mac
- [U] User's Guide
- Contents
- Stata basics
- Elements of Stata
- 11 Language syntax
- 12 Data
- 13 Functions and expressions
- 13.1 Overview
- 13.2 Operators
- 13.3 Functions
- 13.4 System variables (_variables)
- 13.5 Accessing coefficients and standard errors
- 13.6 Accessing results from Stata commands
- 13.7 Explicit subscripting
- 13.8 Indicator values for levels of factor variables
- 13.9 Time-series operators
- 13.10 Label values
- 13.11 Precision and problems therein
- 13.12 References
- 14 Matrix expressions
- 14.1 Overview
- 14.2 Row and column names
- 14.3 Vectors and scalars
- 14.4 Inputting matrices by hand
- 14.5 Accessing matrices created by Stata commands
- 14.6 Creating matrices by accumulating data
- 14.7 Matrix operators
- 14.8 Matrix functions
- 14.9 Subscripting
- 14.10 Using matrices in scalar expressions
- 14.11 Reference
- 15 Saving and printing output---log files
- 16 Do-files
- 17 Ado-files
- 17.1 Description
- 17.2 What is an ado-file?
- 17.3 How can I tell if a command is built in or an ado-file?
- 17.4 How can I look at an ado-file?
- 17.5 Where does Stata look for ado-files?
- 17.6 How do I install an addition?
- 17.7 How do I add my own ado-files?
- 17.8 How do I install official updates?
- 17.9 How do I install updates to user-written additions?
- 17.10 Reference
- 18 Programming Stata
- 18.1 Description
- 18.2 Relationship between a program and a do-file
- 18.3 Macros
- 18.4 Program arguments
- 18.5 Scalars and matrices
- 18.6 Temporarily destroying the data in memory
- 18.7 Temporary objects
- 18.8 Accessing results calculated by other programs
- 18.9 Accessing results calculated by estimation commands
- 18.10 Storing results
- 18.11 Ado-files
- 18.12 Tools for interacting with programs outside Stata and with other languages
- 18.13 A compendium of useful commands for programmers
- 18.14 References
- 19 Immediate commands
- 20 Estimation and postestimation commands
- 20.1 All estimation commands work the same way
- 20.2 Standard syntax
- 20.3 Replaying prior results
- 20.4 Cataloging estimation results
- 20.5 Saving estimation results
- 20.6 Specifying the estimation subsample
- 20.7 Specifying the width of confidence intervals
- 20.8 Formatting the coefficient table
- 20.9 Obtaining the variance--covariance matrix
- 20.10 Obtaining predicted values
- 20.11 Accessing estimated coefficients
- 20.12 Performing hypothesis tests on the coefficients
- 20.13 Obtaining linear combinations of coefficients
- 20.14 Obtaining nonlinear combinations of coefficients
- 20.15 Obtaining marginal means, adjusted predictions, and predictive margins
- 20.16 Obtaining conditional and average marginal effects
- 20.17 Obtaining pairwise comparisons
- 20.18 Obtaining contrasts, tests of interactions, and main effects
- 20.19 Graphing margins, marginal effects, and contrasts
- 20.20 Dynamic forecasts and simulations
- 20.21 Obtaining robust variance estimates
- 20.22 Obtaining scores
- 20.23 Weighted estimation
- 20.24 A list of postestimation commands
- 20.25 References
- Advice
- 21 Entering and importing data
- 22 Combining datasets
- 23 Working with strings
- 24 Working with dates and times
- 25 Working with categorical data and factor variables
- 26 Overview of Stata estimation commands
- 26.1 Introduction
- 26.2 Means, proportions, and related statistics
- 26.3 Linear regression with simple error structures
- 26.4 Structural equation modeling (SEM)
- 26.5 ANOVA, ANCOVA, MANOVA, and MANCOVA
- 26.6 Generalized linear models
- 26.7 Binary-outcome qualitative dependent-variable models
- 26.8 ROC analysis
- 26.9 Conditional logistic regression
- 26.10 Multiple-outcome qualitative dependent-variable models
- 26.11 Count dependent-variable models
- 26.12 Exact estimators
- 26.13 Linear regression with heteroskedastic errors
- 26.14 Stochastic frontier models
- 26.15 Regression with systems of equations
- 26.16 Models with endogenous sample selection
- 26.17 Models with time-series data
- 26.18 Panel-data models
- 26.19 Multilevel mixed-effects models
- 26.20 Survival-time (failure-time) models
- 26.21 Treatment-effect models
- 26.22 Generalized method of moments (GMM)
- 26.23 Estimation with correlated errors
- 26.24 Survey data
- 26.25 Multiple imputation
- 26.26 Multivariate and cluster analysis
- 26.27 Pharmacokinetic data
- 26.28 Specification search tools
- 26.29 Power and sample-size analysis
- 26.30 Obtaining new estimation commands
- 26.31 References
- 27 Commands everyone should know
- 28 Using the Internet to keep up to date
- Subject and author index
- [D] Data Management
- Contents
- intro
- data management
- append
- assert
- bcal
- by
- cd
- cf
- changeeol
- checksum
- clear
- clonevar
- codebook
- collapse
- compare
- compress
- contract
- copy
- corr2data
- count
- cross
- data types
- datasignature
- datetime
- Syntax
- Types of dates and their human readable forms (HRFs)
- Stata internal form (SIF)
- HRF-to-SIF conversion functions
- Displaying SIFs in HRF
- Building SIFs from components
- SIF-to-SIF conversion
- Extracting time-of-day components from SIFs
- Extracting date components from SIFs
- Conveniently typing SIF values
- Obtaining and working with durations
- Using dates and times from other software
- Description
- Remarks and examples
- References
- Also see
- Syntax
- datetime business calendars
- datetime business calendars creation
- Syntax
- Description
- Remarks and examples
- Introduction
- Concepts
- The preliminary commands
- The omit commands: from/to and if
- The omit commands: and
- The omit commands: omit date
- The omit commands: omit dayofweek
- The omit commands: omit dowinmonth
- Creating stbcal-files with bcal create
- Where to place stbcal-files
- How to debug stbcal-files
- Ideas for calendars that may not occur to you
- Also see
- datetime display formats
- datetime translation
- Syntax
- Description
- Remarks and examples
- Introduction
- Specifying the mask
- How the HRF-to-SIF functions interpret the mask
- Working with two-digit years
- Working with incomplete dates and times
- Translating run-together dates, such as 20060125
- Valid times
- The clock() and Clock() functions
- Why there are two SIF datetime encodings
- Advice on using datetime/c and datetime/C
- Determining when leap seconds occurred
- The date() function
- The other translation functions
- Also see
- describe
- destring
- dir
- drawnorm
- drop
- ds
- duplicates
- edit
- egen
- encode
- erase
- expand
- expandcl
- export
- filefilter
- fillin
- format
- functions
- Description
- Mathematical functions
- Probability distributions and density functions
- Beta and noncentral beta distributions
- ibeta()
- betaden()
- ibetatail()
- invibeta()
- invibetatail()
- nibeta()
- invnibeta()
- Binomial distribution
- binomial()
- binomialp()
- binomialtail()
- invbinomial()
- invbinomialtail()
- Chi-squared and noncentral chi-squared distributions
- chi2()
- chi2den()
- chi2tail()
- invchi2()
- invchi2tail()
- nchi2()
- nchi2den()
- nchi2tail()
- invnchi2()
- invnchi2tail()
- npnchi2()
- Dunnett's multiple range distribution
- dunnettprob()
- invdunnettprob()
- F and noncentral F distributions
- F()
- Fden()
- Ftail()
- invF()
- invFtail()
- nF()
- nFtail()
- invnFtail()
- npnF()
- Gamma distribution
- gammap()
- gammaden()
- gammaptail()
- invgammap()
- invgammaptail()
- dgammapda()
- dgammapdada()
- dgammapdadx()
- dgammapdx()
- dgammapdxdx()
- Hypergeometric distribution
- hypergeometric()
- hypergeometricp()
- Negative binomial distribution
- nbinomial()
- nbinomialp()
- nbinomialtail()
- invnbinomial()
- invnbinomiailtail()
- Normal (Gaussian), log of the normal, and binormal distributions
- binormal()
- normal()
- normalden()
- invnormal()
- lnnormal()
- Poisson distribution
- poisson()
- poissonp()
- poissontail()
- invpoisson()
- invpoissontail()
- Student's t and noncentral Student's t distributions
- t()
- tden()
- ttail()
- invt()
- invttail()
- nt()
- ntden()
- nttail()
- invnttail()
- npnt()
- Tukey's Studentized range distribution
- tukeyprob()
- invtukeyprob()
- Random-number functions
- String functions
- abbrev()
- char()
- indexnot()
- itrim()
- length()
- lower()
- ltrim()
- plural()
- proper()
- real()
- regexm()
- regexr()
- regexs()
- reverse()
- rtrim()
- soundex()
- soundex_nara()
- strcat()
- strdup()
- string()
- strlen()
- strlower()
- strltrim()
- strmatch()
- strofreal()
- strpos()
- strproper()
- strreverse()
- strrtrim()
- strtoname()
- strtrim()
- strupper()
- subinstr()
- subinword()
- substr()
- trim()
- upper()
- word()
- wordcount()
- Programming functions
- autocode()
- byteorder()
- c()
- _caller()
- chop()
- clip()
- cond()
- e()
- e(sample)
- epsdouble()
- epsfloat()
- fileexists()
- fileread()
- filereaderror()
- filewrite()
- float()
- fmtwidth()
- has_eprop()
- inlist()
- inrange()
- irecode()
- matrix()
- maxbyte()
- maxdouble()
- maxfloat()
- maxint()
- maxlong()
- mi()
- minbyte()
- mindouble()
- minfloat()
- minint()
- minlong()
- missing()
- r()
- recode()
- replay()
- return()
- s()
- scalar()
- smallestdouble()
- Date and time functions
- bofd()
- Cdhms()
- clock()
- Cmdyhms()
- Cofc()
- cofC()
- Cofd()
- cofd()
- daily()
- date()
- day()
- dhms()
- dofb()
- dofC()
- dofc()
- dofh()
- dofm()
- dofq()
- dofw()
- dofy()
- dow()
- doy()
- halfyear()
- halfyearly()
- hh()
- hhC()
- hms()
- hofd()
- hours()
- mdy()
- mdyhms()
- minutes()
- mm()
- mmC()
- mofd()
- month()
- monthly()
- msofhours()
- msofminutes()
- msofseconds()
- qofd()
- quarter()
- quarterly()
- seconds()
- ss()
- ssC()
- tC()
- tc()
- td()
- th()
- tm()
- tq()
- tw()
- week()
- weekly()
- wofd()
- year()
- yearly()
- yh()
- ym()
- yofd()
- yq()
- yw()
- Selecting time spans
- Matrix functions returning a matrix
- Matrix functions returning a scalar
- Acknowledgments
- References
- Also see
- Description
- generate
- gsort
- hexdump
- icd9
- import
- import delimited
- import excel
- import haver
- import sasxport
- infile (fixed format)
- infile (free format)
- infix (fixed format)
- input
- inspect
- ipolate
- isid
- joinby
- label
- label language
- labelbook
- list
- lookfor
- memory
- merge
- missing values
- mkdir
- mvencode
- notes
- obs
- odbc
- order
- outfile
- pctile
- putmata
- range
- recast
- recode
- rename
- rename group
- reshape
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Description of basic syntax
- Wide and long data forms
- Avoiding and correcting mistakes
- reshape long and reshape wide without arguments
- Missing variables
- Advanced issues with basic syntax: i()
- Advanced issues with basic syntax: j()
- Advanced issues with basic syntax: xij
- Advanced issues with basic syntax: String identifiers for j()
- Advanced issues with basic syntax: Second-level nesting
- Description of advanced syntax
- Stored results
- Acknowledgment
- References
- Also see
- rmdir
- sample
- save
- separate
- shell
- snapshot
- sort
- split
- stack
- statsby
- sysuse
- type
- use
- varmanage
- webuse
- xmlsave
- xpose
- zipfile
- Subject and author index
- [G] Graphics
- Contents
- Introduction
- Commands
- graph
- graph bar
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Examples of syntax
- Treatment of bars
- Treatment of data
- Obtaining frequencies
- Multiple bars (overlapping the bars)
- Controlling the text of the legend
- Multiple over()s (repeating the bars)
- Nested over()s
- Charts with many categories
- How bars are ordered
- Reordering the bars
- Putting the bars in a prespecified order
- Putting the bars in height order
- Putting the bars in a derived order
- Reordering the bars, example
- Use with by()
- Video example
- History
- References
- Also see
- graph box
- graph combine
- graph copy
- graph describe
- graph dir
- graph display
- graph dot
- graph drop
- graph export
- graph manipulation
- graph matrix
- graph other
- graph pie
- graph play
- graph print
- graph query
- graph rename
- graph save
- graph set
- graph twoway
- graph twoway area
- graph twoway bar
- graph twoway connected
- graph twoway contour
- graph twoway contourline
- graph twoway dot
- graph twoway dropline
- graph twoway fpfit
- graph twoway fpfitci
- graph twoway function
- graph twoway histogram
- graph twoway kdensity
- graph twoway lfit
- graph twoway lfitci
- graph twoway line
- graph twoway lowess
- graph twoway lpoly
- graph twoway lpolyci
- graph twoway mband
- graph twoway mspline
- graph twoway pcarrow
- graph twoway pcarrowi
- graph twoway pccapsym
- graph twoway pci
- graph twoway pcscatter
- graph twoway pcspike
- graph twoway qfit
- graph twoway qfitci
- graph twoway rarea
- graph twoway rbar
- graph twoway rcap
- graph twoway rcapsym
- graph twoway rconnected
- graph twoway rline
- graph twoway rscatter
- graph twoway rspike
- graph twoway scatter
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Typical use
- Scatter syntax
- The overall look for the graph
- The size and aspect ratio of the graph
- Titles
- Axis titles
- Axis labels and ticking
- Grid lines
- Added lines
- Axis range
- Log scales
- Multiple axes
- Markers
- Weighted markers
- Jittered markers
- Connected lines
- Graphs by groups
- Saving graphs
- Video example
- Appendix: Styles and composite styles
- References
- Also see
- graph twoway scatteri
- graph twoway spike
- graph twoway tsline
- graph use
- palette
- set graphics
- set printcolor
- set scheme
- Options
- added_line_options
- added_text_options
- addplot_option
- advanced_options
- area_options
- aspect_option
- axis_choice_options
- Syntax
- Description
- Options
- Remarks and examples
- Usual case: one set of axes
- Special case: multiple axes due to multiple scales
- yaxis(1) and xaxis(1) are the defaults
- Notation style is irrelevant
- yaxis() and xaxis() are plot options
- Specifying the other axes options with multiple axes
- Each plot may have at most one x scale and one y scale
- Special case: Multiple axes with a shared scale
- Reference
- Also see
- axis_label_options
- axis_options
- axis_scale_options
- axis_title_options
- barlook_options
- blabel_option
- by_option
- cat_axis_label_options
- cat_axis_line_options
- clegend_option
- cline_options
- connect_options
- eps_options
- fcline_options
- fitarea_options
- legend_options
- line_options
- marker_label_options
- marker_options
- name_option
- nodraw_option
- play_option
- png_options
- pr_options
- ps_options
- rcap_options
- region_options
- rspike_options
- saving_option
- scale_option
- scheme_option
- std_options
- textbox_options
- tif_options
- title_options
- twoway_options
- Styles/concepts/schemes
- addedlinestyle
- alignmentstyle
- anglestyle
- areastyle
- axisstyle
- bystyle
- clockposstyle
- colorstyle
- compassdirstyle
- concept: gph files
- concept: lines
- concept: repeated options
- connectstyle
- gridstyle
- intensitystyle
- justificationstyle
- legendstyle
- linepatternstyle
- linestyle
- linewidthstyle
- marginstyle
- markerlabelstyle
- markersizestyle
- markerstyle
- orientationstyle
- plotregionstyle
- pstyle
- relativesize
- ringposstyle
- schemes intro
- scheme economist
- scheme s1
- scheme s2
- scheme sj
- shadestyle
- stylelists
- symbolstyle
- text
- textboxstyle
- textsizestyle
- textstyle
- ticksetstyle
- tickstyle
- Subject and author index
- [ME] Multilevel Mixed Effects
- Contents
- me
- mecloglog
- mecloglog postestimation
- meglm
- meglm postestimation
- melogit
- melogit postestimation
- menbreg
- menbreg postestimation
- meologit
- meologit postestimation
- meoprobit
- meoprobit postestimation
- mepoisson
- mepoisson postestimation
- meprobit
- meprobit postestimation
- meqrlogit
- meqrlogit postestimation
- meqrpoisson
- meqrpoisson postestimation
- mixed
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Two-level models
- Covariance structures
- Likelihood versus restricted likelihood
- Three-level models
- Blocked-diagonal covariance structures
- Heteroskedastic random effects
- Heteroskedastic residual errors
- Other residual-error structures
- Crossed-effects models
- Diagnosing convergence problems
- Survey data
- Stored results
- Methods and formulas
- Acknowledgments
- References
- Also see
- mixed postestimation
- Glossary
- Subject and author index
- [MI] Multiple Imputation
- Contents
- intro substantive
- intro
- estimation
- mi add
- mi append
- mi convert
- mi copy
- mi describe
- mi erase
- mi estimate
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Using mi estimate
- Example 1: Completed-data logistic analysis
- Example 2: Completed-data linear regression analysis
- Example 3: Completed-data survival analysis
- Example 4: Panel data and multilevel models
- Example 5: Estimating transformations
- Example 6: Monte Carlo error estimates
- Potential problems that can arise when using mi estimate
- Stored results
- Methods and formulas
- Acknowledgments
- References
- Also see
- mi estimate using
- mi estimate postestimation
- mi expand
- mi export
- mi export ice
- mi export nhanes1
- mi extract
- mi import
- mi import flong
- mi import flongsep
- mi import ice
- mi import nhanes1
- mi import wide
- mi impute
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Stored results
- Methods and formulas
- References
- Also see
- mi impute chained
- mi impute intreg
- mi impute logit
- mi impute mlogit
- mi impute monotone
- mi impute mvn
- mi impute nbreg
- mi impute ologit
- mi impute pmm
- mi impute poisson
- mi impute regress
- mi impute truncreg
- mi merge
- mi misstable
- mi passive
- mi predict
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Using mi predict and mi predictnl
- Example 1: Obtain MI linear predictions and other statistics
- Example 2: Obtain MI linear predictions for the estimation sample
- Example 3: Obtain MI estimates of probabilities
- Example 4: Obtain other MI predictions
- Example 5: Obtain MI predictions after multiple-equation commands
- Methods and formulas
- References
- Also see
- mi ptrace
- mi rename
- mi replace0
- mi reset
- mi reshape
- mi select
- mi set
- mi stsplit
- mi test
- mi update
- mi varying
- mi xeq
- mi XXXset
- noupdate option
- styles
- technical
- Description
- Remarks and examples
- Notation
- Definition of styles
- Adding new commands to mi
- Outline for new commands
- Utility routines
- u_mi_assert_set
- u_mi_certify_data
- u_mi_no_sys_vars and u_mi_no_wide_vars
- u_mi_zap_chars
- u_mi_xeq_on_tmp_flongsep
- u_mi_get_flongsep_tmpname
- mata: u_mi_flongsep_erase()
- u_mi_sortback
- u_mi_save and u_mi_use
- mata: u_mi_wide_swapvars()
- u_mi_fixchars
- mata: u_mi_cpchars_get() and mata: u_mi_cpchars_put()
- mata: u_mi_get_mata_instanced_var()
- mata: u_mi_ptrace_*()
- How to write other set commands to work with mi
- Also see
- workflow
- Glossary
- Subject and author index
- [MV] Multivariate Statistics
- Contents
- intro
- multivariate
- alpha
- biplot
- ca
- ca postestimation
- ca postestimation plots
- candisc
- canon
- canon postestimation
- cluster
- Syntax
- Description
- Remarks and examples
- Introduction to cluster analysis
- Stata's cluster-analysis system
- Data transformations and variable selection
- Similarity and dissimilarity measures
- Partition cluster-analysis methods
- Hierarchical cluster-analysis methods
- Hierarchical cluster analysis applied to a dissimilarity matrix
- Postclustering commands
- Cluster-management tools
- References
- Also see
- clustermat
- cluster dendrogram
- cluster generate
- cluster kmeans and kmedians
- cluster linkage
- cluster notes
- cluster programming subroutines
- cluster programming utilities
- cluster stop
- cluster utility
- discrim
- discrim estat
- discrim knn
- discrim knn postestimation
- discrim lda
- discrim lda postestimation
- discrim logistic
- discrim logistic postestimation
- discrim qda
- discrim qda postestimation
- factor
- factor postestimation
- hotelling
- manova
- manova postestimation
- matrix dissimilarity
- mca
- mca postestimation
- mca postestimation plots
- mds
- mds postestimation
- mds postestimation plots
- mdslong
- mdsmat
- measure_option
- mvreg
- mvreg postestimation
- mvtest
- mvtest correlations
- mvtest covariances
- mvtest means
- mvtest normality
- pca
- pca postestimation
- procrustes
- procrustes postestimation
- rotate
- rotatemat
- scoreplot
- screeplot
- Glossary
- Subject and author index
- [PSS] Power and Sample Size
- Contents
- intro
- GUI
- power
- power, graph
- power, table
- power onemean
- power twomeans
- power pairedmeans
- power oneproportion
- power twoproportions
- power pairedproportions
- power onevariance
- power twovariances
- power onecorrelation
- power twocorrelations
- power oneway
- power twoway
- power repeated
- unbalanced designs
- Glossary
- Subject and author index
- [R] Base Reference
- Contents
- Introduction
- A
- about
- adoupdate
- ameans
- anova
- anova postestimation
- areg
- areg postestimation
- asclogit
- asclogit postestimation
- asmprobit
- asmprobit postestimation
- asroprobit
- asroprobit postestimation
- B
- C
- centile
- ci
- clogit
- clogit postestimation
- cloglog
- cloglog postestimation
- cls
- cnsreg
- cnsreg postestimation
- constraint
- contrast
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Stored results
- Methods and formulas
- References
- Also see
- contrast postestimation
- copyright
- copyright apache
- copyright boost
- copyright freetype
- copyright icu
- copyright jagpdf
- copyright lapack
- copyright libpng
- copyright miglayout
- copyright scintilla
- copyright ttf2pt1
- copyright zlib
- correlate
- cumul
- cusum
- D
- E
- eform_option
- eivreg
- eivreg postestimation
- error messages
- esize
- estat
- estat classification
- estat gof
- estat ic
- estat summarize
- estat vce
- estimates
- estimates describe
- estimates for
- estimates notes
- estimates replay
- estimates save
- estimates stats
- estimates store
- estimates table
- estimates title
- estimation options
- exit
- exlogistic
- exlogistic postestimation
- expoisson
- expoisson postestimation
- F
- G
- gllamm
- glm
- glm postestimation
- glogit
- glogit postestimation
- gmm
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Substitutable expressions
- The weight matrix and two-step estimation
- Obtaining standard errors
- Exponential (Poisson) regression models
- Specifying derivatives
- Exponential regression models with panel data
- Rational-expectations models
- System estimators
- Dynamic panel-data models
- Details of moment-evaluator programs
- Stored results
- Methods and formulas
- References
- Also see
- gmm postestimation
- grmeanby
- H
- hausman
- heckman
- heckman postestimation
- heckoprobit
- heckoprobit postestimation
- heckprobit
- heckprobit postestimation
- help
- hetprobit
- hetprobit postestimation
- histogram
- I
- icc
- inequality
- intreg
- intreg postestimation
- ivpoisson
- ivpoisson postestimation
- ivprobit
- ivprobit postestimation
- ivregress
- ivregress postestimation
- ivtobit
- ivtobit postestimation
- J
- K
- L
- ladder
- level
- limits
- lincom
- linktest
- lnskew0
- log
- logistic
- logistic postestimation
- Description
- Syntax for predict
- Menu for predict
- Options for predict
- Remarks and examples
- predict without options
- predict with the xb and stdp options
- predict with the residuals option
- predict with the number option
- predict with the deviance option
- predict with the rstandard option
- predict with the hat option
- predict with the dx2 option
- predict with the ddeviance option
- predict with the dbeta option
- Methods and formulas
- References
- Also see
- logit
- logit postestimation
- loneway
- lowess
- lpoly
- lroc
- lrtest
- lsens
- lv
- M
- margins
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Obtaining margins of responses
- Example 1: A simple case after regress
- Example 2: A simple case after logistic
- Example 3: Average response versus response at average
- Example 4: Multiple margins from one command
- Example 5: Margins with interaction terms
- Example 6: Margins with continuous variables
- Example 7: Margins of continuous variables
- Example 8: Margins of interactions
- Example 9: Decomposing margins
- Example 10: Testing margins---contrasts of margins
- Example 11: Margins of a specified prediction
- Example 12: Margins of a specified expression
- Example 13: Margins with multiple outcomes (responses)
- Example 14: Margins with multiple equations
- Example 15: Margins evaluated out of sample
- Obtaining margins of derivatives of responses (a.k.a. marginal effects)
- Do not specify marginlist when you mean over()
- Use at() freely, especially with continuous variables
- Expressing derivatives as elasticities
- Derivatives versus discrete differences
- Example 16: Average marginal effect (partial effects)
- Example 17: Average marginal effect of all covariates
- Example 18: Evaluating marginal effects over the response surface
- Obtaining margins with survey data and representative samples
- Standardizing margins
- Obtaining margins as though the data were balanced
- Obtaining margins with nested designs
- Special topics
- Video examples
- Glossary
- Stored results
- Methods and formulas
- References
- Also see
- margins postestimation
- margins, contrast
- margins, pwcompare
- marginsplot
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Dataset
- Profile plots
- Interaction plots
- Contrasts of margins---effects (discrete marginal effects)
- Three-way interactions
- Continuous covariates
- Plots at every value of a continuous covariate
- Contrasts of at() groups---discrete effects
- Controlling the graph's dimensions
- Pairwise comparisons
- Horizontal is sometimes better
- Marginal effects
- Plotting a subset of the results from margins
- Advanced usage
- Video examples
- Addendum: Advanced uses of dimlist
- Acknowledgments
- References
- Also see
- matsize
- maximize
- mean
- mean postestimation
- meta
- mfp
- mfp postestimation
- misstable
- mkspline
- ml
- Syntax
- Description
- Options
- Options for use with ml model in interactive or noninteractive mode
- Options for use with ml model in noninteractive mode
- Options for use when specifying equations
- Options for use with ml search
- Option for use with ml plot
- Options for use with ml init
- Options for use with ml maximize
- Option for use with ml graph
- Options for use with ml display
- Options for use with mleval
- Option for use with mlsum
- Option for use with mlvecsum
- Option for use with mlmatsum
- Options for use with mlmatbysum
- Options for use with ml score
- Remarks and examples
- Stored results
- Methods and formulas
- References
- Also see
- mlexp
- mlexp postestimation
- mlogit
- mlogit postestimation
- more
- mprobit
- mprobit postestimation
- margins
- N
- nbreg
- nbreg postestimation
- nestreg
- net
- Syntax
- Description
- Options
- Remarks and examples
- Definition of a package
- The purpose of the net and ado commands
- Content pages
- Package-description pages
- Where packages are installed
- A summary of the net command
- A summary of the ado command
- Relationship of net and ado to the point-and-click interface
- Creating your own site
- Format of content and package-description files
- Example 1
- Example 2
- Additional package directives
- SMCL in content and package-description files
- Error-free file delivery
- References
- Also see
- net search
- netio
- news
- nl
- nl postestimation
- nlcom
- nlogit
- nlogit postestimation
- nlsur
- nlsur postestimation
- nptrend
- O
- P
- pcorr
- permute
- pk
- pkcollapse
- pkcross
- pkequiv
- pkexamine
- pkshape
- pksumm
- poisson
- poisson postestimation
- predict
- predictnl
- probit
- probit postestimation
- proportion
- proportion postestimation
- prtest
- pwcompare
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Stored results
- Methods and formulas
- References
- Also see
- pwcompare postestimation
- pwmean
- pwmean postestimation
- Q
- R
- ranksum
- ratio
- ratio postestimation
- reg3
- reg3 postestimation
- regress
- regress postestimation
- Description
- Predictions
- DFBETA influence statistics
- Tests for violation of assumptions
- Syntax for estat hettest
- Menu for estat
- Description for estat hettest
- Options for estat hettest
- Syntax for estat imtest
- Menu for estat
- Description for estat imtest
- Options for estat imtest
- Syntax for estat ovtest
- Menu for estat
- Description for estat ovtest
- Option for estat ovtest
- Syntax for estat szroeter
- Menu for estat
- Description for estat szroeter
- Options for estat szroeter
- Remarks and examples for estat hettest, estat imtest, estat ovtest, and estat szroeter
- Stored results for estat hettest, estat imtest, and estat ovtest
- Variance inflation factors
- Measures of effect size
- Methods and formulas
- Acknowledgments
- References
- Also see
- regress postestimation diagnostic plots
- regress postestimation time series
- #review
- roc
- roccomp
- rocfit
- rocfit postestimation
- rocreg
- rocreg postestimation
- rocregplot
- roctab
- rologit
- rologit postestimation
- rreg
- rreg postestimation
- runtest
- S
- T
- U
- V
- W
- X
- Z
- Author index
- Subject index
- [SEM] Structural Equation Modeling
- Contents
- Acknowledgments
- intro 1
- intro 2
- Description
- Remarks and examples
- Using path diagrams to specify standard linear SEMs
- Specifying correlation
- Using the command language to specify standard linear SEMs
- Specifying generalized SEMs: Family and link
- Specifying generalized SEMs: Family and link, multinomial logistic regression
- Specifying generalized SEMs: Family and link, paths from response variables
- Specifying generalized SEMs: Multilevel mixed effects (2 levels)
- Specifying generalized SEMs: Multilevel mixed effects (3 levels)
- Specifying generalized SEMs: Multilevel mixed effects (4+ levels)
- Specifying generalized SEMs: Multilevel mixed effects with random intercepts
- Specifying generalized SEMs: Multilevel mixed effects with random slopes
- Reference
- Also see
- intro 3
- intro 4
- Description
- Remarks and examples
- Differences in assumptions between sem and gsem
- sem: Choice of estimation method
- gsem: Choice of estimation method
- Treatment of missing values
- Variable types: Observed, latent, endogenous, exogenous, and error
- Constraining parameters
- Identification 1: Substantive issues
- Identification 2: Normalization constraints (anchoring)
- References
- Also see
- intro 5
- Description
- Remarks and examples
- Single-factor measurement models
- Item--response theory (IRT) models
- Multiple-factor measurement models
- Confirmatory factor analysis (CFA) models
- Structural models 1: Linear regression
- Structural models 2: Gamma regression
- Structural models 3: Binary-outcome models
- Structural models 4: Count models
- Structural models 5: Ordinal models
- Structural models 6: Multinomial logistic regression
- Structural models 7: Dependencies between response variables
- Structural models 8: Unobserved inputs, outputs, or both
- Structural models 9: MIMIC models
- Structural models 10: Seemingly unrelated regression (SUR)
- Structural models 11: Multivariate regression
- Structural models 12: Mediation models
- Correlations
- Higher-order CFA models
- Correlated uniqueness model
- Latent growth models
- Models with reliability
- Multilevel mixed-effects models
- References
- Also see
- intro 6
- Description
- Remarks and examples
- The generic SEM model
- Fitting the model for different groups of the data
- Which parameters vary by default, and which do not
- Specifying which parameters are allowed to vary in broad, sweeping terms
- Adding constraints for path coefficients across groups
- Adding constraints for means, variances, or covariances across groups
- Adding constraints for some groups but not others
- Adding paths for some groups but not others
- Relaxing constraints
- Reference
- Also see
- intro 7
- Description
- Remarks and examples
- Replaying the model (sem and gsem)
- Displaying odds ratios, incidence-rate ratios, etc. (gsem only)
- Obtaining goodness-of-fit statistics (sem and gsem)
- Performing tests for including omitted paths and relaxing constraints (sem only)
- Performing tests of model simplification (sem and gsem)
- Displaying other results, statistics, and tests (sem and gsem)
- Obtaining predicted values (sem)
- Obtaining predicted values (gsem)
- Using contrast, pwcompare, and margins (sem and gsem)
- Accessing stored results
- Also see
- intro 8
- intro 9
- intro 10
- intro 11
- intro 12
- Description
- Remarks and examples
- Is your model identified?
- Convergence solutions generically described
- Temporarily eliminate option reliability()
- Use default normalization constraints
- Temporarily eliminate feedback loops
- Temporarily simplify the model
- Try other numerical integration methods (gsem only)
- Get better starting values (sem and gsem)
- Get better starting values (gsem)
- Also see
- Builder
- Builder, generalized
- estat eform
- estat eqgof
- estat eqtest
- estat framework
- estat ggof
- estat ginvariant
- estat gof
- estat mindices
- estat residuals
- estat scoretests
- estat stable
- estat stdize
- estat summarize
- estat teffects
- example 1
- example 2
- example 3
- example 4
- example 5
- example 6
- example 7
- example 8
- example 9
- example 10
- example 11
- example 12
- example 13
- example 14
- example 15
- example 16
- example 17
- example 18
- example 19
- example 20
- example 21
- example 22
- example 23
- example 24
- example 25
- example 26
- example 27g
- example 28g
- example 29g
- example 30g
- example 31g
- example 32g
- example 33g
- example 34g
- example 35g
- example 36g
- example 37g
- example 38g
- Description
- Remarks and examples
- Random-intercept model, single-equation formulation
- Random-intercept model, within-and-between formulation
- Random-slope model, single-equation formulation
- Random-slope model, within-and-between formulation
- Fitting the random-intercept model with the Builder
- Fitting the random-slope model with the Builder
- Reference
- Also see
- example 39g
- example 40g
- example 41g
- example 42g
- example 43g
- example 44g
- example 45g
- example 46g
- gsem
- gsem estimation options
- gsem family-and-link options
- gsem model description options
- gsem path notation extensions
- gsem postestimation
- gsem reporting options
- lincom
- lrtest
- methods and formulas for gsem
- methods and formulas for sem
- nlcom
- predict after gsem
- predict after sem
- sem
- sem and gsem option constraints()
- sem and gsem option covstructure()
- sem and gsem option from()
- sem and gsem option reliability()
- sem and gsem path notation
- sem and gsem syntax options
- sem estimation options
- sem group options
- sem model description options
- sem option method()
- sem option noxconditional
- sem option select()
- sem path notation extensions
- sem postestimation
- sem reporting options
- sem ssd options
- ssd
- test
- testnl
- Glossary
- Subject and author index
- [ST] Survival Analysis
- Contents
- intro
- survival analysis
- Description
- Remarks and examples
- Introduction
- Declaring and converting count data
- Converting snapshot data
- Declaring and summarizing survival-time data
- Manipulating survival-time data
- Obtaining summary statistics, confidence intervals, tables, etc.
- Fitting regression models
- Sample size and power determination for survival analysis
- Converting survival-time data
- Programmer's utilities
- Epidemiological tables
- Reference
- Also see
- ct
- ctset
- cttost
- discrete
- epitab
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Incidence-rate data
- Stratified incidence-rate data
- Standardized estimates with stratified incidence-rate data
- Cumulative incidence data
- Stratified cumulative incidence data
- Standardized estimates with stratified cumulative incidence data
- Case--control data
- Stratified case--control data
- Case--control data with multiple levels of exposure
- Case--control data with confounders and possibly multiple levels of exposure
- Standardized estimates with stratified case--control data
- Matched case--control data
- Video examples
- Stored results
- Methods and formulas
- Unstratified incidence-rate data (ir and iri)
- Unstratified cumulative incidence data (cs and csi)
- Unstratified case--control data (cc and cci)
- Unstratified matched case--control data (mcc and mcci)
- Stratified incidence-rate data (ir with the by() option)
- Stratified cumulative incidence data (cs with the by() option)
- Stratified case--control data (cc with by() option, mhodds, tabodds)
- Acknowledgments
- References
- Also see
- ltable
- snapspan
- st
- st_is
- stbase
- stci
- stcox
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Cox regression with uncensored data
- Cox regression with censored data
- Treatment of tied failure times
- Cox regression with discrete time-varying covariates
- Cox regression with continuous time-varying covariates
- Robust estimate of variance
- Cox regression with multiple-failure data
- Stratified estimation
- Cox regression as Poisson regression
- Cox regression with shared frailty
- Stored results
- Methods and formulas
- Acknowledgment
- References
- Also see
- stcox PH-assumption tests
- stcox postestimation
- stcrreg
- stcrreg postestimation
- stcurve
- stdescribe
- stfill
- stgen
- stir
- stpower
- stpower cox
- stpower exponential
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Introduction
- Other ways of specifying the effect size
- Sample-size determination by using different approximations
- Sample-size determination in the presence of censoring
- Nonuniform accrual and exponential losses to follow-up
- The conditional versus unconditional approaches
- Link to the sample-size and power computation for the log-rank test
- Power determination
- Stored results
- Methods and formulas
- References
- Also see
- stpower logrank
- stptime
- strate
- streg
- streg postestimation
- sts
- sts generate
- sts graph
- sts list
- sts test
- stset
- Syntax
- Menu
- Description
- Options for use with stset and streset
- Options unique to streset
- Options for st
- Remarks and examples
- What are survival-time data?
- Key concepts
- Survival-time datasets
- Using stset
- Two concepts of time
- The substantive meaning of analysis time
- Setting the failure event
- Setting multiple failures
- First entry times
- Final exit times
- Intermediate exit and reentry times (gaps)
- if() versus if exp
- Past and future records
- Using streset
- Performance and multiple-record-per-subject datasets
- Sequencing of events within t
- Weights
- Data warnings and errors flagged by stset
- Using survival-time data in Stata
- References
- Also see
- stsplit
- stsum
- sttocc
- sttoct
- stvary
- Glossary
- Subject and author index
- [SVY] Survey Data
- Contents
- intro
- survey
- bootstrap_options
- brr_options
- direct standardization
- estat
- jackknife_options
- ml for svy
- poststratification
- sdr_options
- subpopulation estimation
- svy
- svy bootstrap
- svy brr
- svy estimation
- svy jackknife
- svy postestimation
- svy sdr
- svy: tabulate oneway
- svy: tabulate twoway
- svydescribe
- svymarkout
- svyset
- variance estimation
- Glossary
- Subject and author index
- [TE] Treatment Effects
- Contents
- treatment effects
- etpoisson
- etpoisson postestimation
- etregress
- etregress postestimation
- teffects
- teffects intro
- teffects intro advanced
- Description
- Remarks and examples
- Introduction
- Defining treatment effects
- The potential-outcome model
- Assumptions needed for estimation
- Comparing the ATE and ATET
- Overview of treatment-effect estimators
- RA estimators
- IPW estimators
- AIPW estimators
- IPWRA estimators
- Nearest-neighbor matching estimators
- Propensity-score matching estimators
- Choosing among estimators
- Model choice
- Acknowledgments
- References
- Also see
- teffects aipw
- teffects ipw
- teffects ipwra
- teffects multivalued
- teffects nnmatch
- teffects overlap
- teffects postestimation
- teffects psmatch
- teffects ra
- Glossary
- Subject and author index
- [TS] Time Series
- Contents
- intro
- time series
- arch
- arch postestimation
- arfima
- arfima postestimation
- arima
- arima postestimation
- corrgram
- cumsp
- dfactor
- dfactor postestimation
- dfgls
- dfuller
- estat acplot
- estat aroots
- fcast compute
- fcast graph
- forecast
- forecast adjust
- forecast clear
- forecast coefvector
- forecast create
- forecast describe
- forecast drop
- forecast estimates
- forecast exogenous
- forecast identity
- forecast list
- forecast query
- forecast solve
- irf
- irf add
- irf cgraph
- irf create
- Syntax
- Menu
- Description
- Options
- Remarks and examples
- Methods and formulas
- Impulse--response function formulas for VARs
- Dynamic-multiplier function formulas for VARs
- Forecast-error variance decomposition formulas for VARs
- Impulse{--}response function formulas for VECMs
- Algorithms for bootstrapping the VAR IRF and FEVD standard errors
- Impulse--response function formulas for ARIMA and ARFIMA
- References
- Also see
- irf ctable
- irf describe
- irf drop
- irf graph
- irf ograph
- irf rename
- irf set
- irf table
- mgarch
- mgarch ccc
- mgarch ccc postestimation
- mgarch dcc
- mgarch dcc postestimation
- mgarch dvech
- mgarch dvech postestimation
- mgarch vcc
- mgarch vcc postestimation
- newey
- newey postestimation
- pergram
- pperron
- prais
- prais postestimation
- psdensity
- rolling
- sspace
- sspace postestimation
- tsappend
- tsfill
- tsfilter
- Syntax
- Description
- Remarks and examples
- An example dataset
- A baseline method: Symmetric moving-average (SMA) filters
- An overview of filtering in the frequency domain
- SMA revisited: The Baxter--King filter
- Filtering a random walk: The Christiano--Fitzgerald filter
- A one-parameter high-pass filter: The Hodrick--Prescott filter
- A two-parameter high-pass filter: The Butterworth filter
- Methods and formulas
- Acknowledgments
- References
- Also see
- tsfilter bk
- tsfilter bw
- tsfilter cf
- tsfilter hp
- tsline
- tsreport
- tsrevar
- tsset
- tssmooth
- tssmooth dexponential
- tssmooth exponential
- tssmooth hwinters
- tssmooth ma
- tssmooth nl
- tssmooth shwinters
- ucm
- ucm postestimation
- var intro
- var
- var postestimation
- var svar
- var svar postestimation
- varbasic
- varbasic postestimation
- vargranger
- varlmar
- varnorm
- varsoc
- varstable
- varwle
- vec intro
- vec
- vec postestimation
- veclmar
- vecnorm
- vecrank
- vecstable
- wntestb
- wntestq
- xcorr
- Glossary
- Subject and author index
- [XT] Longitudinal Data/Panel Data
- Contents
- intro
- xt
- quadchk
- vce_options
- xtabond
- xtabond postestimation
- xtcloglog
- xtcloglog postestimation
- xtdata
- xtdescribe
- xtdpd
- xtdpd postestimation
- xtdpdsys
- xtdpdsys postestimation
- xtfrontier
- xtfrontier postestimation
- xtgee
- xtgee postestimation
- xtgls
- xtgls postestimation
- xthtaylor
- xthtaylor postestimation
- xtintreg
- xtintreg postestimation
- xtivreg
- xtivreg postestimation
- xtline
- xtlogit
- xtlogit postestimation
- xtnbreg
- xtnbreg postestimation
- xtologit
- xtologit postestimation
- xtoprobit
- xtoprobit postestimation
- xtpcse
- xtpcse postestimation
- xtpoisson
- xtpoisson postestimation
- xtprobit
- xtprobit postestimation
- xtrc
- xtrc postestimation
- xtreg
- xtreg postestimation
- xtregar
- xtregar postestimation
- xtset
- xtsum
- xttab
- xttobit
- xttobit postestimation
- xtunitroot
- Glossary
- Subject and author index
- [P] Programming
- Contents
- Combined subject table of contents
- intro
- automation
- break
- byable
- capture
- char
- class
- Description
- Remarks and examples
- 1. Introduction
- 2. Definitions
- 3. Version control
- 4. Member variables
- 5. Inheritance
- 6. Member programs' return values
- 7. Assignment
- 8. Built-ins
- 9. Prefix operators
- 10. Using object values
- 11. Object destruction
- 12. Advanced topics
- Appendix A. Finding, loading, and clearing class definitions
- Appendix B. Jargon
- Appendix C. Syntax diagrams
- Also see
- class exit
- classutil
- comments
- confirm
- continue
- creturn
- _datasignature
- #delimit
- dialog programming
- Description
- Remarks and examples
- 1. Introduction
- 2. Concepts
- 3. Commands
- 3.1 VERSION
- 3.2 INCLUDE
- 3.3 DEFINE
- 3.4 POSITION
- 3.5 LIST
- 3.6 DIALOG
- 3.6.1 CHECKBOX on/off input control
- 3.6.2 RADIO on/off input control
- 3.6.3 SPINNER numeric input control
- 3.6.4 EDIT string input control
- 3.6.5 VARLIST and VARNAME string input controls
- 3.6.6 FILE string input control
- 3.6.7 LISTBOX list input control
- 3.6.8 COMBOBOX list input control
- 3.6.9 BUTTON special input control
- 3.6.10 TEXT static control
- 3.6.11 TEXTBOX static control
- 3.6.12 GROUPBOX static control
- 3.6.13 FRAME static control
- 3.6.14 COLOR input control
- 3.6.15 EXP expression input control
- 3.6.16 HLINK hyperlink input control
- 3.7 OK, SUBMIT, CANCEL, and COPY u-action buttons
- 3.8 HELP and RESET helper buttons
- 3.9 Special dialog directives
- 4. SCRIPT
- 5. PROGRAM
- 5.1 Concepts
- 5.1.1 Vnames
- 5.1.2 Enames
- 5.1.3 rstrings: cmdstring and optstring
- 5.1.4 Adding to an rstring
- 5.2 Flow-control commands
- 5.2.1 if
- 5.2.2 while
- 5.2.3 call
- 5.2.4 exit
- 5.2.5 close
- 5.3 Error-checking and presentation commands
- 5.3.1 require
- 5.3.2 stopbox
- 5.4 Command-construction commands
- 5.4.1 by
- 5.4.2 bysort
- 5.4.3 put
- 5.4.4 varlist
- 5.4.5 ifexp
- 5.4.6 inrange
- 5.4.7 weight
- 5.4.8 beginoptions and endoptions
- 5.4.8.1 option
- 5.4.8.2 optionarg
- 5.5 Command-execution commands
- 5.5.1 stata
- 5.5.2 clear
- 5.6 Special scripts and programs
- 6. Properties
- 7. Child dialogs
- 7.1 Referencing the parent
- 8. Example
- Appendix A: Jargon
- Appendix B: Class definition of dialog boxes
- Appendix C: Interface guidelines for dialog boxes
- Frequently asked questions
- Also see
- discard
- display
- ereturn
- error
- estat programming
- _estimates
- exit
- file
- Syntax
- Description
- Options
- Remarks and examples
- Use of file
- Use of file with tempfiles
- Writing ASCII text files
- Reading ASCII text files
- Use of seek when writing or reading ASCII text files
- Writing and reading binary files
- Writing binary files
- Reading binary files
- Use of seek when writing or reading binary files
- Appendix A.1 $mskip hinmuskip $ Useful commands and functions for use with file
- Appendix A.2 $mskip hinmuskip $ Actions of binary output formats with out-of-range values
- Stored results
- Reference
- Also see
- file formats .dta
- findfile
- foreach
- Syntax
- Description
- Remarks and examples
- Introduction
- foreach { elax $mathsurround hbox {$Z$}@ mathinner {ldotp ldotp ldotp }mskip hinmuskip $} of local and foreach { elax $mathsurround hbox {$Z$}@ mathinner {ldotp ldotp ldotp }mskip hinmuskip $} of global
- foreach { elax $mathsurround hbox {$Z$}@ mathinner {ldotp ldotp ldotp }mskip hinmuskip $} of varlist
- foreach { elax $mathsurround hbox {$Z$}@ mathinner {ldotp ldotp ldotp }mskip hinmuskip $} of newlist
- foreach { elax $mathsurround hbox {$Z$}@ mathinner {ldotp ldotp ldotp }mskip hinmuskip $} of numlist
- Use of foreach with continue
- The unprocessed list elements
- Also see
- forvalues
- fvexpand
- gettoken
- if
- include
- java
- javacall
- levelsof
- macro
- Syntax
- Description
- Remarks and examples
- Formal definition of a macro
- Global and local macro names
- Macro assignment
- Macro extended functions
- Macro extended function for extracting program properties
- Macro extended functions for extracting data attributes
- Macro extended function for naming variables
- Macro extended functions for filenames and file paths
- Macro extended function for accessing operating-system parameters
- Macro extended functions for names of stored results
- Macro extended function for formatting results
- Macro extended function for manipulating lists
- Macro extended functions related to matrices
- Macro extended function related to time-series operators
- Macro extended function for copying a macro
- Macro extended functions for parsing
- Macro expansion operators and function
- The tempvar, tempname, and tempfile commands
- Manipulation of macros
- Macros as arguments
- Also see
- macro lists
- makecns
- mark
- matlist
- matrix
- matrix accum
- matrix define
- matrix dissimilarity
- matrix eigenvalues
- matrix get
- matrix mkmat
- matrix rownames
- matrix score
- matrix svd
- matrix symeigen
- matrix utility
- more
- nopreserve option
- numlist
- pause
- plugin
- postfile
- _predict
- preserve
- program
- program properties
- Project Manager
- putexcel
- quietly
- _return
- return
- _rmcoll
- rmsg
- _robust
- scalar
- serset
- signestimationsample
- sleep
- smcl
- Description
- Remarks and examples
- Introduction
- SMCL modes
- Command summary---general syntax
- Help file preprocessor directive for substituting repeated material
- Formatting directives for use in line and paragraph modes
- Link directives for use in line and paragraph modes
- Formatting directives for use in line mode
- Formatting directives for use in paragraph mode
- Directive for entering the as-is mode
- Directive for entering the Stata 6 help mode
- Inserting values from constant and current-value class
- Displaying characters using ASCII code
- Advice on using display
- Advice on formatting help files
- Also see
- sortpreserve
- syntax
- sysdir
- tabdisp
- timer
- tokenize
- trace
- unab
- unabcmd
- varabbrev
- version
- viewsource
- while
- window programming
- window fopen
- window manage
- Syntax
- Description
- Remarks and examples
- Also see
- window menu
- Syntax
- Description
- Remarks and examples
- Overview
- Clear previously defined menu additions
- Define submenus
- Define menu items
- Define separator bars
- Activate menu changes
- Add files to the Open Recent menu
- Keyboard shortcuts (Windows only)
- Examples
- Advanced features: Dialogs and built-in actions
- Advanced features: Creating checked menu items
- Putting it all together
- Also see
- window push
- window stopbox
- Subject and author index
- [M] Mata
- Contents
- Introduction to the Mata manual
- Introduction and advice
- intro
- ado
- first
- Description
- Remarks and examples
- Invoking Mata
- Using Mata
- Making mistakes: Interpreting error messages
- Working with real numbers, complex numbers, and strings
- Working with scalars, vectors, and matrices
- Working with functions
- Distinguishing real and complex values
- Working with matrix and scalar functions
- Performing element-by-element calculations: Colon operators
- Writing programs
- More functions
- Mata environment commands
- Exiting Mata
- Also see
- help
- how
- interactive
- Description
- Remarks and examples
- 1. Start in Stata; load the data
- 2. Create any time-series variables
- 3. Create a constant variable
- 4. Drop unnecessary variables
- 5. Drop observations with missing values
- 6. Put variables on roughly the same numeric scale
- 7. Enter Mata
- 8. Use Mata's st_view() function to access your data
- 9. Perform your matrix calculations
- Review
- Reference
- Also see
- LAPACK
- limits
- naming
- permutation
- returnedargs
- source
- tolerance
- Language definition
- intro
- break
- class
- Syntax
- Description
- Remarks and examples
- Notation and jargon
- Declaring and defining a class
- Saving classes in files
- Workflow recommendation
- When you need to recompile
- Obtaining instances of a class
- Constructors and destructors
- Setting member variable and member function exposure
- Making a member final
- Making a member static
- Virtual functions
- Referring to the current class using this
- Using super to access the parent's concept
- Casting back to a parent
- Accessing external functions from member functions
- Pointers to classes
- Also see
- comments
- continue
- declarations
- do
- errors
- exp
- for
- ftof
- goto
- if
- op_arith
- op_assignment
- op_colon
- op_conditional
- op_increment
- op_join
- op_kronecker
- op_logical
- op_range
- op_transpose
- optargs
- pointers
- pragma
- reswords
- return
- semicolons
- struct
- Syntax
- Description
- Remarks and examples
- Introduction
- Structures and functions must have different names
- Structure variables must be explicitly declared
- Declare structure variables to be scalars whenever possible
- Vectors and matrices of structures
- Structures of structures
- Pointers to structures
- Operators and functions for use with structure members
- Operators and functions for use with entire structures
- Listing structures
- Use of transmorphics as passthrus
- Saving compiled structure definitions
- Saving structure variables
- Reference
- Also see
- subscripts
- syntax
- version
- void
- while
- Commands for controlling Mata
- Index and guide to functions
- Mata functions
- intro
- abbrev()
- abs()
- adosubdir()
- all()
- args()
- asarray()
- ascii()
- assert()
- blockdiag()
- bufio()
- byteorder()
- C()
- c()
- callersversion()
- cat()
- chdir()
- cholesky()
- cholinv()
- cholsolve()
- comb()
- cond()
- conj()
- corr()
- cross()
- crossdev()
- cvpermute()
- date()
- deriv()
- designmatrix()
- det()
- _diag()
- diag()
- diag0cnt()
- diagonal()
- dir()
- direxists()
- direxternal()
- display()
- displayas()
- displayflush()
- Dmatrix()
- _docx*()
- dsign()
- e()
- editmissing()
- edittoint()
- edittozero()
- editvalue()
- eigensystem()
- eigensystemselect()
- eltype()
- epsilon()
- _equilrc()
- error()
- errprintf()
- exit()
- exp()
- factorial()
- favorspeed()
- ferrortext()
- fft()
- fileexists()
- _fillmissing()
- findexternal()
- findfile()
- floatround()
- fmtwidth()
- fopen()
- fullsvd()
- geigensystem()
- ghessenbergd()
- ghk()
- ghkfast()
- gschurd()
- halton()
- hash1()
- hessenbergd()
- Hilbert()
- I()
- inbase()
- indexnot()
- invorder()
- invsym()
- invtokens()
- isdiagonal()
- isfleeting()
- isreal()
- isrealvalues()
- issymmetric()
- isview()
- J()
- Kmatrix()
- lapack()
- liststruct()
- Lmatrix()
- logit()
- lowertriangle()
- lud()
- luinv()
- lusolve()
- makesymmetric()
- matexpsym()
- matpowersym()
- mean()
- mindouble()
- minindex()
- minmax()
- missing()
- missingof()
- mod()
- moptimize()
- Syntax
- Step 1: Initialization
- Step 2: Definition of maximization or minimization problem
- Step 3: Perform optimization or perform a single function evaluation
- Step 4: Post, display, or obtain results
- Utility functions for use in all steps
- Definition of M
- Setting the sample
- Specifying dependent variables
- Specifying independent variables
- Specifying constraints
- Specifying weights or survey data
- Specifying clusters and panels
- Specifying optimization technique
- Specifying initial values
- Performing one evaluation of the objective function
- Performing optimization of the objective function
- Tracing optimization
- Specifying convergence criteria
- Accessing results
- Stata evaluators
- Advanced functions
- Syntax of evaluators
- Syntax of type lf evaluators
- Syntax of type d evaluators
- Syntax of type lf* evaluators
- Syntax of type gf evaluators
- Syntax of type q evaluators
- Passing extra information to evaluators
- Utility functions
- Description
- Remarks and examples
- Conformability
- Diagnostics
- References
- Also see
- Syntax
- more()
- _negate()
- norm()
- normal()
- optimize()
- panelsetup()
- pathjoin()
- pinv()
- polyeval()
- printf()
- qrd()
- qrinv()
- qrsolve()
- quadcross()
- range()
- rank()
- Re()
- reldif()
- rows()
- rowshape()
- runiform()
- runningsum()
- schurd()
- select()
- setbreakintr()
- sign()
- sin()
- sizeof()
- solve_tol()
- solvelower()
- solvenl()
- sort()
- soundex()
- spline3()
- sqrt()
- st_addobs()
- st_addvar()
- st_data()
- st_dir()
- st_dropvar()
- st_global()
- st_isfmt()
- st_isname()
- st_local()
- st_macroexpand()
- st_matrix()
- st_numscalar()
- st_nvar()
- st_rclear()
- st_store()
- st_subview()
- st_tempname()
- st_tsrevar()
- st_updata()
- st_varformat()
- st_varindex()
- st_varname()
- st_varrename()
- st_vartype()
- st_view()
- st_viewvars()
- st_vlexists()
- stata()
- stataversion()
- strdup()
- strlen()
- strmatch()
- strofreal()
- strpos()
- strreverse()
- strtoname()
- strtoreal()
- strtrim()
- strupper()
- subinstr()
- sublowertriangle()
- _substr()
- substr()
- sum()
- svd()
- svsolve()
- swap()
- Toeplitz()
- tokenget()
- tokens()
- trace()
- _transpose()
- transposeonly()
- trunc()
- uniqrows()
- unitcircle()
- unlink()
- valofexternal()
- Vandermonde()
- vec()
- xl()
- Mata glossary of common terms
- Subject and author index
- [I] Index
- Subject index