Download STATA STUDY MATERIAL and more Study Guides, Projects, Research Social Sciences in PDF only on Docsity!
This is the complete contents for all manuals. Every estimation command has a postestimation entry; however, not all postestimation entries are listed here.
Getting started Data manipulation and management Basic data commands Reshaping datasets Creating and dropping variables Labeling, display formats, and notes Functions and expressions Changing and renaming variables Strings Examining data Dates and times File manipulation Loading, saving, importing, and exporting data Miscellaneous data commands Combining data Multiple imputation Utilities Basic utilities Internet Error messages Data types and memory Stored results Advanced utilities Graphics Common graphs Survival-analysis graphs Distributional graphs Time-series graphs Item response theory graphs More statistical graphs Multivariate graphs Editing Quality control Graph utilities Regression diagnostic plots Graph schemes ROC analysis Graph concepts Smoothing and densities Statistics ANOVA and related Multidimensional scaling and biplots Basic statistics Multilevel mixed-effects models Bayesian analysis Multiple imputation Binary outcomes Multivariate analysis of variance and Categorical outcomes related techniques Censored and truncated regression models Nonlinear regression Cluster analysis Nonparametric statistics Correspondence analysis Ordinal outcomes Count outcomes Other statistics Discriminant analysis Pharmacokinetic statistics Do-it-yourself generalized method of moments Power and sample size Do-it-yourself maximum likelihood estimation Quality control Endogenous covariates ROC analysis Epidemiology and related Rotation Estimation related Sample selection models Exact statistics Simulation/resampling Factor analysis and principal components Standard postestimation tests, tables, Fractional outcomes and other analyses Generalized linear models Structural equation modeling Indicator and categorical variables Survey data
1
Item response theory Survival analysis Linear regression and related Time series, multivariate Logistic and probit regression Time series, univariate Longitudinal data/panel data Transforms and normality tests Mixed models Treatment effects Matrix commands Basics Other Programming Mata Programming Basics Projects Program control Advanced programming commands Parsing and program arguments Special-interest programming commands Console output File formats Commonly used programming commands Mata Debugging Interface features
Getting started
[GSM] Getting Started with Stata for Mac........................................ [GSU] Getting Started with Stata for Unix....................................... [GSW] Getting Started with Stata for Windows.................................... [U] Chapter 3............................ Resources for learning and using Stata [U] Chapter 4................................. Stata’s help and search facilities [R] help............................................... Display help in Stata [R] search....................... Search Stata documentation and other resources
Data manipulation and management
Basic data commands [D] codebook.......................................... Describe data contents [D] data management................. Introduction to data management commands [D] data types.................................. Quick reference for data types [D] datetime................................. Date and time values and variables [D] describe................................. Describe data in memory or in file [D] edit.................................. Browse or edit data with Data Editor [D] format........................................ Set variables’ output format [D] insobs......................................... Add or insert observations [D] inspect.......................... Display simple summary of data’s attributes [D] label.................................................. Manipulate labels [D] list.............................................. List values of variables [D] missing values........................... Quick reference for missing values [D] rename................................................. Rename variable [D] save.................................................. Save Stata dataset [D] sort......................................................... Sort data [D] use.................................................. Load Stata dataset [D] varmanage................ Manage variable labels, formats, and other properties
Loading, saving, importing, and exporting data
[GS] Chapter 6 (GSM, GSU, GSW)........................ Using the Data Editor [U] Chapter 21................................... Entering and importing data [D] edit.................................. Browse or edit data with Data Editor [D] export............................... Overview of exporting data from Stata [D] import............................... Overview of importing data into Stata [D] import delimited................................. Import delimited text data [D] import excel................................. Import and export Excel files [D] import haver..................... Import data from Haver Analytics databases [D] import sasxport.............. Import and export datasets in SAS XPORT format [D] infile (fixed format)............ Read text data in fixed format with a dictionary [D] infile (free format).............................. Read unformatted text data [D] infix (fixed format)............................ Read text data in fixed format [D] input.......................................... Enter data from keyboard [D] odbc.......................... Load, write, or view data from ODBC sources [D] outfile....................................... Export dataset in text format [P] putexcel..................................... Export results to an Excel file [P] putexcel advanced........ Export results to an Excel file using advanced syntax [D] save.................................................. Save Stata dataset [D] sysuse.............................................. Use shipped dataset [D] use.................................................. Load Stata dataset [D] webuse.................................... Use dataset from Stata website [D] xmlsave............................ Export or import dataset in XML format
Combining data
[U] Chapter 22........................................... Combining datasets [D] append................................................. Append datasets [MI] mi append.............................................. Append mi data [D] cross....................... Form every pairwise combination of two datasets [D] joinby......................... Form all pairwise combinations within groups [D] merge.................................................. Merge datasets [MI] mi merge................................................ Merge mi data
Reshaping datasets
[D] collapse................................. Make dataset of summary statistics [D] contract......................... Make dataset of frequencies and percentages [D] expand............................................ Duplicate observations [D] expandcl.................................. Duplicate clustered observations [D] fillin.............................................. Rectangularize dataset [D] obs.......................... Increase the number of observations in a dataset [D] reshape.................. Convert data from wide to long form and vice versa [MI] mi reshape............................................. Reshape mi data [TS] rolling............................. Rolling-window and recursive estimation [D] separate......................................... Create separate variables [SEM] ssd.............................. Making summary statistics data (sem only) [D] stack....................................................... Stack data [D] statsby....................... Collect statistics for a command across a by list [D] xpose................................ Interchange observations and variables
Labeling, display formats, and notes
[GS] Chapter 7 (GSM, GSU, GSW)................... Using the Variables Manager [U] Section 12.5..................... Formats: Controlling how data are displayed [U] Section 12.6............................. Dataset, variable, and value labels [D] format........................................ Set variables’ output format [D] label.................................................. Manipulate labels [D] label language............ Labels for variables and values in multiple languages [D] labelbook................................................. Label utilities [D] notes................................................ Place notes in data [D] varmanage................ Manage variable labels, formats, and other properties
Changing and renaming variables
[GS] Chapter 7 (GSM, GSU, GSW)................... Using the Variables Manager [U] Chapter 25................. Working with categorical data and factor variables [D] clonevar........................................... Clone existing variable [D] destring............ Convert string variables to numeric variables and vice versa [D] encode............................ Encode string into numeric and vice versa [D] generate............................... Create or change contents of variable [D] mvencode............. Change missing values to numeric values and vice versa [D] order......................................... Reorder variables in dataset [D] recode....................................... Recode categorical variables [D] rename................................................. Rename variable [D] rename group.................................. Rename groups of variables [D] split....................................... Split string variables into parts [D] varmanage................ Manage variable labels, formats, and other properties
Examining data
[GS] Chapter 6 (GSM, GSU, GSW)........................ Using the Data Editor [D] cf................................................ Compare two datasets [D] codebook.......................................... Describe data contents [D] compare........................................... Compare two variables [D] count...................... Count observations satisfying specified conditions [D] describe................................. Describe data in memory or in file [D] ds................ List variables matching name patterns or other characteristics [D] duplicates........................ Report, tag, or drop duplicate observations [D] edit.................................. Browse or edit data with Data Editor [D] gsort...................................... Ascending and descending sort [D] inspect.......................... Display simple summary of data’s attributes [D] isid........................................... Check for unique identifiers [D] lookfor......................... Search for string in variable names and labels [R] lv.................................................. Letter-value displays [R] misstable......................................... Tabulate missing values [MI] mi describe............................................. Describe mi data [MI] mi misstable............................. Tabulate pattern of missing values [D] pctile................................. Create variable containing percentiles [ST] stdescribe..................................... Describe survival-time data [R] summarize............................................ Summary statistics [SVY] svy: tabulate oneway......................... One-way tables for survey data [SVY] svy: tabulate twoway......................... Two-way tables for survey data [P] tabdisp................................................... Display tables [R] table................................... Flexible table of summary statistics
[MI] mi merge................................................ Merge mi data [MI] mi misstable............................. Tabulate pattern of missing values [MI] mi passive..................... Generate/replace and register passive variables [MI] mi ptrace............................... Load parameter-trace file into Stata [MI] mi rename.............................................. Rename variable [MI] mi replace0......................................... Replace original data [MI] mi reset................................. Reset imputed or passive variables [MI] mi reshape............................................. Reshape mi data [MI] mi set.................................... Declare multiple-imputation data [MI] mi stsplit........................................ Stsplit and stjoin mi data [MI] mi update............................... Ensure that mi data are consistent [MI] mi varying..................... Identify variables that vary across imputations [MI] mi xeq........................ Execute command(s) on individual imputations [MI] mi XXXset......................... Declare mi data to be svy, st, ts, xt, etc. [MI] noupdate option...................................... The noupdate option [MI] styles.................................................... Dataset styles [MI] workflow............................................ Suggested workflow
Utilities
Basic utilities [GS] Chapter 13 (GSM, GSU, GSW)...... Using the Do-file Editor—automating Stata [U] Chapter 4................................. Stata’s help and search facilities [U] Chapter 15............................ Saving and printing output—log files [U] Chapter 16.................................................... Do-files [R] about................................. Display information about your Stata [D] by............................ Repeat Stata command on subsets of the data [R] cls................................................ Clear Results window [R] copyright.................................... Display copyright information [R] do........................................ Execute commands from a file [R] doedit.................................... Edit do-files and other text files [R] exit......................................................... Exit Stata [R] help............................................... Display help in Stata [R] level.......................................... Set default confidence level [R] log.......................................... Echo copy of session to file [D] obs.......................... Increase the number of observations in a dataset [R] postest............................................ Postestimation Selector [R] #review....................................... Review previous commands [R] search....................... Search Stata documentation and other resources [BAYES] set clevel........................................ Set default credible level [R] translate........................................... Print and translate logs [D] unicode translate................................. Translate files to Unicode [R] view................................................. View files and logs [D] zipfile...... Compress and uncompress files and directories in zip archive format
Error messages [U] Chapter 8................................. Error messages and return codes [P] error................................ Display generic error message and exit [R] error messages............................. Error messages and return codes [P] rmsg.................................................. Return messages
Stored results
[U] Section 13.5....................... Accessing coefficients and standard errors [U] Section 18.8................... Accessing results calculated by other programs [U] Section 18.9............. Accessing results calculated by estimation commands [U] Section 18.10............................................. Storing results [P] creturn............................................. Return c-class values [P] ereturn......................................... Post the estimation results [R] estimates............................. Save and manipulate estimation results [R] estimates describe............................... Describe estimation results [R] estimates for................... Repeat postestimation command across models [R] estimates notes.............................. Add notes to estimation results [R] estimates replay................................ Redisplay estimation results [R] estimates save............................... Save and use estimation results [R] estimates stats.................................... Model-selection statistics [R] estimates store........................... Store and restore estimation results [R] estimates table................................. Compare estimation results [R] estimates title................................ Set title for estimation results [P] return............................................ Preserve stored results [P] return............................................... Return stored results [R] stored results.............................................. Stored results
Internet
[U] Chapter 28............................ Using the Internet to keep up to date [R] adoupdate.................................... Update user-written ado-files [D] checksum...................................... Calculate checksum of file [D] copy......................................... Copy file from disk or URL [R] net................. Install and manage user-written additions from the Internet [R] net search........................ Search the Internet for installable packages [R] netio........................................ Control Internet connections [R] news................................................. Report Stata news [R] sj............................ Stata Journal and STB installation instructions [R] ssc................................ Install and uninstall packages from SSC [R] update......................................... Check for official updates [D] use.................................................. Load Stata dataset
Data types and memory
[U] Chapter 6............................................ Managing memory [U] Section 12.2.2...................................... Numeric storage types [U] Section 12.4.................................................... Strings [U] Section 12.4.2.................................... Handling Unicode strings [U] Section 13.12............................... Precision and problems therein [U] Chapter 23......................................... Working with strings [D] compress....................................... Compress data in memory [D] data types.................................. Quick reference for data types [R] matsize.................... Set the maximum number of variables in a model [D] memory............................................ Memory management [D] missing values........................... Quick reference for missing values [D] recast..................................... Change storage type of variable
[G-2] graph copy....................................... Copy graph in memory [G-2] graph describe............... Describe contents of graph in memory or on disk [G-2] graph dir....................... List names of graphs in memory and on disk [G-2] graph display.............................. Display graph stored in memory [G-2] graph dot................................... Dot charts (summary statistics) [G-2] graph drop.................................... Drop graphs from memory [G-2] graph export........................................ Export current graph [G-2] graph manipulation........................... Graph manipulation commands [G-2] graph matrix.............................................. Matrix graphs [G-2] graph other..................................... Other graphics commands [G-2] graph pie..................................................... Pie charts [G-2] graph play..................... Apply edits from a recording on current graph [G-2] graph print................................................ Print a graph [G-2] graph query............................... List available schemes and styles [G-2] graph rename................................... Rename graph in memory [G-2] graph replay...................................... Replay multiple graphs [G-2] graph save............................................ Save graph to disk [G-2] graph set............................................ Set graphics options [G-2] graph twoway............................................ Twoway graphs [G-2] graph twoway area....................... Twoway line plot with area shading [G-2] graph twoway bar....................................... Twoway bar plots [G-2] graph twoway connected........................... Twoway connected plots [G-2] graph twoway contour................. Twoway contour plot with area shading [G-2] graph twoway contourline.......................... Twoway contour-line plot [G-2] graph twoway dot....................................... Twoway dot plots [G-2] graph twoway dropline........................... Twoway dropped-line plots [G-2] graph twoway fpfit.............. Twoway fractional-polynomial prediction plots [G-2] graph twoway fpfitci.... Twoway fractional-polynomial prediction plots with CIs [G-2] graph twoway function......................... Twoway line plot of function [G-2] graph twoway histogram................................... Histogram plots [G-2] graph twoway kdensity................................ Kernel density plots [G-2] graph twoway lfit............................ Twoway linear prediction plots [G-2] graph twoway lfitci................... Twoway linear prediction plots with CIs [G-2] graph twoway line..................................... Twoway line plots [G-2] graph twoway lowess.............................. Local linear smooth plots [G-2] graph twoway lpoly.......................... Local polynomial smooth plots [G-2] graph twoway lpolyci................. Local polynomial smooth plots with CIs [G-2] graph twoway mband............................ Twoway median-band plots [G-2] graph twoway mspline.......................... Twoway median-spline plots [G-2] graph twoway pcarrow..................... Paired-coordinate plot with arrows [G-2] graph twoway pcarrowi............ Twoway pcarrow with immediate arguments [G-2] graph twoway pccapsym.. Paired-coordinate plot with spikes and marker symbols [G-2] graph twoway pci...... Twoway paired-coordinate plot with immediate arguments [G-2] graph twoway pcscatter................... Paired-coordinate plot with markers [G-2] graph twoway pcspike...................... Paired-coordinate plot with spikes [G-2] graph twoway qfit......................... Twoway quadratic prediction plots [G-2] graph twoway qfitci............... Twoway quadratic prediction plots with CIs [G-2] graph twoway rarea........................... Range plot with area shading [G-2] graph twoway rbar................................... Range plot with bars [G-2] graph twoway rcap........................... Range plot with capped spikes [G-2] graph twoway rcapsym..... Range plot with spikes capped with marker symbols
[G-2] graph twoway rconnected.................... Range plot with connected lines [G-2] graph twoway rline................................... Range plot with lines [G-2] graph twoway rscatter............................. Range plot with markers [G-2] graph twoway rspike................................ Range plot with spikes [G-2] graph twoway scatter.................................. Twoway scatterplots [G-2] graph twoway scatteri...................... Scatter with immediate arguments [G-2] graph twoway spike................................... Twoway spike plots [G-2] graph twoway tsline.................................... Twoway line plots [G-2] graph use.................................... Display graph stored on disk [R] histogram................. Histograms for continuous and categorical variables [R] marginsplot.................... Graph results from margins (profile plots, etc.) [G-2] palette............................... Display palettes of available selections
Distributional graphs
[R] cumul........................................... Cumulative distribution [R] diagnostic plots............................... Distributional diagnostic plots [R] dotplot.......................................... Comparative scatterplots [R] histogram................. Histograms for continuous and categorical variables [R] ladder................................................ Ladder of powers [R] spikeplot...................................... Spike plots and rootograms [R] sunflower............................... Density-distribution sunflower plots
Item response theory graphs
[MV] biplot.......................................................... Biplots [IRT] irtgraph icc................................... Item characteristic curve plot [IRT] irtgraph iif................................... Item information function plot [IRT] irtgraph tcc................................... Test characteristic curve plot [IRT] irtgraph tif................................... Test information function plot
Multivariate graphs
[MV] biplot.......................................................... Biplots [MV] ca postestimation...................... Postestimation tools for ca and camat [MV] ca postestimation plots.................. Postestimation plots for ca and camat [MV] cluster dendrogram............... Dendrograms for hierarchical cluster analysis [MV] mca postestimation............................. Postestimation tools for mca [MV] mca postestimation plots........................ Postestimation plots for mca [MV] mds postestimation.......... Postestimation tools for mds, mdsmat, and mdslong [MV] mds postestimation plots..... Postestimation plots for mds, mdsmat, and mdslong [MV] procrustes postestimation................... Postestimation tools for procrustes [MV] scoreplot......................................... Score and loading plots [MV] screeplot.................................................... Scree plot
Quality control
[R] cusum............................ Cusum plots and tests for binary variables [R] qc................................................. Quality control charts [R] serrbar..................................... Graph standard error bar chart
Regression diagnostic plots
[R] regress postestimation diagnostic plots........... Postestimation plots for regress
[R] stem.............................................. Stem-and-leaf displays [TE] teffects overlap............................................. Overlap plots [XT] xtline............................................... Panel-data line plots
Editing [G-1] graph editor............................................... Graph Editor
Graph utilities [G-2] set graphics............................... Set whether graphs are displayed [G-2] set printcolor............... Set how colors are treated when graphs are printed [G-2] set scheme........................................... Set default scheme
Graph schemes [G-4] schemes intro..................................... Introduction to schemes [G-4] scheme economist........................... Scheme description: economist [G-4] scheme s1................................... Scheme description: s1 family [G-4] scheme s2................................... Scheme description: s2 family [G-4] scheme sj......................................... Scheme description: sj
Graph concepts [G-4] concept: gph files......................................... Using gph files [G-4] concept: lines............................................... Using lines [G-4] concept: repeated options................... Interpretation of repeated options [G-4] text..................................................... Text in graphs
Statistics
ANOVA and related [U] Chapter 26......................... Overview of Stata estimation commands [R] anova.................................. Analysis of variance and covariance [R] contrast.................. Contrasts and linear hypothesis tests after estimation [R] icc....................................... Intraclass correlation coefficients [R] loneway................ Large one-way ANOVA, random effects, and reliability [MV] manova...................... Multivariate analysis of variance and covariance [ME] meglm...................... Multilevel mixed-effects generalized linear model [ME] mixed............................ Multilevel mixed-effects linear regression [R] oneway..................................... One-way analysis of variance [R] pkcross.................................... Analyze crossover experiments [R] pkshape......................... Reshape (pharmacokinetic) Latin-square data [R] pwcompare......................................... Pairwise comparisons [R] regress................................................ Linear regression [XT] xtreg Fixed-, between-, and random-effects and population-averaged linear models
Basic statistics [R] anova.................................. Analysis of variance and covariance [R] bitest........................................... Binomial probability test [R] ci.................. Confidence intervals for means, proportions, and variances [R] correlate................. Correlations (covariances) of variables or coefficients [D] egen.............................................. Extensions to generate
[R] esize................................ Effect size based on mean comparison [R] icc....................................... Intraclass correlation coefficients [R] mean................................................... Estimate means [R] misstable......................................... Tabulate missing values [MV] mvtest................................................. Multivariate tests [R] oneway..................................... One-way analysis of variance [R] proportion........................................... Estimate proportions [R] prtest............................................... Tests of proportions [R] pwmean.................................... Pairwise comparisons of means [R] ranksum.................................. Equality tests on unmatched data [R] ratio.................................................... Estimate ratios [R] regress................................................ Linear regression [R] sdtest.......................................... Variance-comparison tests [R] signrank.................................... Equality tests on matched data [D] statsby....................... Collect statistics for a command across a by list [R] summarize............................................ Summary statistics [R] table................................... Flexible table of summary statistics [R] tabstat................................. Compact table of summary statistics [R] tabulate oneway.............................. One-way table of frequencies [R] tabulate twoway.............................. Two-way table of frequencies [R] tabulate, summarize()............ One- and two-way tables of summary statistics [R] total..................................................... Estimate totals [R] ttest....................................... t tests (mean-comparison tests) [R] ztest........................ z tests (mean-comparison tests, known variance)
Bayesian analysis
[BAYES] bayes........................ Introduction to commands for Bayesian analysis [BAYES] bayesgraph................. Graphical summaries and convergence diagnostics [BAYES] bayesmh............. Bayesian regression using Metropolis–Hastings algorithm [BAYES] bayesmh evaluators.................... User-defined evaluators with bayesmh [BAYES] bayesmh postestimation..................... Postestimation tools for bayesmh [BAYES] bayesstats................................ Bayesian statistics after bayesmh [BAYES] bayesstats ess..................... Effective sample sizes and related statistics [BAYES] bayesstats ic.................. Bayesian information criteria and Bayes factors [BAYES] bayesstats summary............................ Bayesian summary statistics [BAYES] bayestest...................................... Bayesian hypothesis testing [BAYES] bayestest interval................................ Interval hypothesis testing [BAYES] bayestest model.......... Hypothesis testing using model posterior probabilities
Binary outcomes
[U] Chapter 20......................... Estimation and postestimation commands [U] Section 26.7............. Binary-outcome qualitative dependent-variable models [R] binreg............ Generalized linear models: Extensions to the binomial family [R] biprobit........................................ Bivariate probit regression [R] cloglog................................. Complementary log-log regression [TE] eteffects............................ Endogenous treatment-effects estimation [R] exlogistic........................................ Exact logistic regression [R] glm........................................... Generalized linear models [R] heckprobit.............................. Probit model with sample selection [R] hetprobit..................................... Heteroskedastic probit model [IRT] irt 1pl...................................... One-parameter logistic model
[XT] xtintreg....................... Random-effects interval-data regression models [XT] xtstreg........................... Random-effects parametric survival models [XT] xttobit....................................... Random-effects tobit models
Cluster analysis
[U] Section 26.28.............................. Multivariate and cluster analysis [MV] cluster............................ Introduction to cluster-analysis commands [MV] cluster dendrogram............... Dendrograms for hierarchical cluster analysis [MV] cluster generate.. Generate summary or grouping variables from a cluster analysis [MV] cluster kmeans and kmedians............ Kmeans and kmedians cluster analysis [MV] cluster linkage................................ Hierarchical cluster analysis [MV] cluster notes................................. Place notes in cluster analysis [MV] cluster programming subroutines.................. Add cluster-analysis routines [MV] cluster programming utilities............. Cluster-analysis programming utilities [MV] cluster stop................................. Cluster-analysis stopping rules [MV] cluster utility..................... List, rename, use, and drop cluster analyses [MV] clustermat............................. Introduction to clustermat commands [MV] matrix dissimilarity............... Compute similarity or dissimilarity measures [MV] measure option............... Option for similarity and dissimilarity measures [MV] multivariate........................... Introduction to multivariate commands
Correspondence analysis
[MV] ca........................................ Simple correspondence analysis [MV] mca............................. Multiple and joint correspondence analysis
Count outcomes
[U] Chapter 20......................... Estimation and postestimation commands [U] Section 26.13............................. Count dependent-variable models [U] Section 26.20.5............... Count dependent-variable models with panel data [R] cpoisson..................................... Censored Poisson regression [TE] eteffects............................ Endogenous treatment-effects estimation [TE] etpoisson................. Poisson regression with endogenous treatment effects [R] expoisson....................................... Exact Poisson regression [ME] menbreg................. Multilevel mixed-effects negative binomial regression [ME] mepoisson........................ Multilevel mixed-effects Poisson regression [ME] meqrpoisson.... Multilevel mixed-effects Poisson regression (QR decomposition) [R] nbreg........................................ Negative binomial regression [R] poisson.............................................. Poisson regression [TE] teffects aipw........................ Augmented inverse-probability weighting [TE] teffects ipw................................... Inverse-probability weighting [TE] teffects ipwra............... Inverse-probability-weighted regression adjustment [TE] teffects nnmatch................................. Nearest-neighbor matching [TE] teffects psmatch................................. Propensity-score matching [TE] teffects ra......................................... Regression adjustment [R] tnbreg.............................. Truncated negative binomial regression [R] tpoisson...................................... Truncated Poisson regression [XT] xtnbreg Fixed-effects, random-effects, & population-averaged negative binomial models [XT] xtpoisson.. Fixed-effects, random-effects, and population-averaged Poisson models [R] zinb.............................. Zero-inflated negative binomial regression [R] zip....................................... Zero-inflated Poisson regression
Discriminant analysis
[MV] candisc.............................. Canonical linear discriminant analysis [MV] discrim............................................ Discriminant analysis [MV] discrim estat............................... Postestimation tools for discrim [MV] discrim knn........................ kth-nearest-neighbor discriminant analysis [MV] discrim lda................................... Linear discriminant analysis [MV] discrim logistic............................... Logistic discriminant analysis [MV] discrim qda................................. Quadratic discriminant analysis [MV] scoreplot......................................... Score and loading plots [MV] screeplot.................................................... Scree plot
Do-it-yourself generalized method of moments
[U] Section 26.24....................... Generalized method of moments (GMM) [R] gmm............................ Generalized method of moments estimation [P] matrix................................... Introduction to matrix commands
Do-it-yourself maximum likelihood estimation
[P] matrix................................... Introduction to matrix commands [R] ml....................................... Maximum likelihood estimation [R] mlexp............ Maximum likelihood estimation of user-specified expressions
Endogenous covariates
[U] Chapter 20......................... Estimation and postestimation commands [U] Chapter 26......................... Overview of Stata estimation commands [TE] eteffects............................ Endogenous treatment-effects estimation [TE] etpoisson................. Poisson regression with endogenous treatment effects [TE] etregress.................. Linear regression with endogenous treatment effects [TS] forecast.................................... Econometric model forecasting [R] gmm............................ Generalized method of moments estimation [R] ivpoisson................ Poisson model with continuous endogenous covariates [R] ivprobit.................. Probit model with continuous endogenous covariates [R] ivregress.................... Single-equation instrumental-variables regression [R] ivtobit.................... Tobit model with continuous endogenous covariates [R] reg3.............. Three-stage estimation for systems of simultaneous equations [XT] xtabond.................. Arellano–Bond linear dynamic panel-data estimation [XT] xtdpd................................. Linear dynamic panel-data estimation [XT] xtdpdsys.... Arellano–Bover/Blundell–Bond linear dynamic panel-data estimation [XT] xthtaylor.............. Hausman–Taylor estimator for error-components models [XT] xtivreg... Instrumental variables and two-stage least squares for panel-data models
Epidemiology and related
[R] binreg............ Generalized linear models: Extensions to the binomial family [R] brier........................................... Brier score decomposition [R] clogit........................... Conditional (fixed-effects) logistic regression [R] dstdize.................................. Direct and indirect standardization [R] epitab.......................................... Tables for epidemiologists [R] exlogistic........................................ Exact logistic regression [D] icd........................................ Introduction to ICD commands [D] icd10............................................ ICD-10 diagnosis codes [D] icd9.............................. ICD-9-CM diagnosis and procedure codes
Factor analysis and principal components
[MV] alpha........ Compute interitem correlations (covariances) and Cronbach’s alpha [MV] canon............................................. Canonical correlations [MV] factor................................................... Factor analysis [MV] pca.......................................... Principal component analysis [MV] rotate.................... Orthogonal and oblique rotations after factor and pca [MV] rotatemat................... Orthogonal and oblique rotations of a Stata matrix [MV] scoreplot......................................... Score and loading plots [MV] screeplot.................................................... Scree plot [R] tetrachoric........................ Tetrachoric correlations for binary variables
Fractional outcomes
[R] betareg.................................................. Beta regression [TE] eteffects............................ Endogenous treatment-effects estimation [R] fracreg...................................... Fractional response regression [TE] teffects ipw................................... Inverse-probability weighting [TE] teffects nnmatch................................. Nearest-neighbor matching [TE] teffects psmatch................................. Propensity-score matching
Generalized linear models
[U] Chapter 20......................... Estimation and postestimation commands [U] Section 26.6.................................... Generalized linear models [R] binreg............ Generalized linear models: Extensions to the binomial family [R] fracreg...................................... Fractional response regression [R] glm........................................... Generalized linear models [XT] xtgee................ Fit population-averaged panel-data models by using GEE
Indicator and categorical variables
[U] Section 11.4.3............................................ Factor variables [U] Chapter 25................. Working with categorical data and factor variables [R] fvset....................................... Declare factor-variable settings
Item response theory
[U] Section 26.12....................................... Item response theory [IRT] Control Panel......................................... IRT Control Panel [IRT] dif.............................. Introduction to differential item functioning [IRT] diflogistic........................................ Logistic regression DIF [IRT] difmh.............................................. Mantel–Haenszel DIF [IRT] estat report............................... Report estimated IRT parameters [IRT] irt 1pl...................................... One-parameter logistic model [IRT] irt 2pl...................................... Two-parameter logistic model [IRT] irt 3pl..................................... Three-parameter logistic model [IRT] irt grm........................................... Graded response model [IRT] irt hybrid............................................. Hybrid IRT models [IRT] irt nrm.......................................... Nominal response model [IRT] irt pcm............................................. Partial credit model [IRT] irt rsm............................................... Rating scale model [IRT] irtgraph icc................................... Item characteristic curve plot [IRT] irtgraph iif................................... Item information function plot [IRT] irtgraph tcc................................... Test characteristic curve plot [IRT] irtgraph tif................................... Test information function plot
Linear regression and related
[U] Chapter 20......................... Estimation and postestimation commands [U] Chapter 26......................... Overview of Stata estimation commands [R] areg....................... Linear regression with a large dummy-variable set [R] cnsreg....................................... Constrained linear regression [R] constraint....................................... Define and list constraints [R] eivreg........................................ Errors-in-variables regression [TE] etpoisson................. Poisson regression with endogenous treatment effects [TE] etregress.................. Linear regression with endogenous treatment effects [R] fp........................................ Fractional polynomial regression [R] frontier........................................ Stochastic frontier models [R] glm........................................... Generalized linear models [R] heckman....................................... Heckman selection model [R] ivpoisson................ Poisson model with continuous endogenous covariates [R] ivregress.................... Single-equation instrumental-variables regression [R] ivtobit.................... Tobit model with continuous endogenous covariates [R] lpoly........................... Kernel-weighted local polynomial smoothing [ME] meglm...................... Multilevel mixed-effects generalized linear model [R] mfp............................. Multivariable fractional polynomial models [ME] mixed............................ Multilevel mixed-effects linear regression [MV] mvreg............................................ Multivariate regression [R] nestreg............................................ Nested model statistics [TS] newey......................... Regression with Newey–West standard errors [TS] prais......................... Prais – Winsten and Cochrane – Orcutt regression [R] qreg................................................. Quantile regression [R] reg3.............. Three-stage estimation for systems of simultaneous equations [R] regress................................................ Linear regression [R] rocfit............................................ Parametric ROC models [R] rreg.................................................. Robust regression [ST] stcox..................................... Cox proportional hazards model [ST] stcrreg........................................ Competing-risks regression [R] stepwise............................................. Stepwise estimation [ST] streg.......................................... Parametric survival models [R] sureg.............................. Zellner’s seemingly unrelated regression [R] tnbreg.............................. Truncated negative binomial regression [R] vwls...................................... Variance-weighted least squares [XT] xtabond.................. Arellano–Bond linear dynamic panel-data estimation [XT] xtdpd................................. Linear dynamic panel-data estimation [XT] xtdpdsys.... Arellano–Bover/Blundell–Bond linear dynamic panel-data estimation [XT] xtgee................ Fit population-averaged panel-data models by using GEE [XT] xtgls.................................. Fit panel-data models by using GLS [XT] xthtaylor.............. Hausman–Taylor estimator for error-components models [XT] xtivreg... Instrumental variables and two-stage least squares for panel-data models [XT] xtpcse.................. Linear regression with panel-corrected standard errors [XT] xtrc.......................................... Random-coefficients model [XT] xtreg Fixed-, between-, and random-effects and population-averaged linear models [XT] xtregar....... Fixed- and random-effects linear models with an AR(1) disturbance [XT] xtstreg........................... Random-effects parametric survival models
