Subject index - Stata

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84 Subject index robust, see gsem option vce(), see sem option vce() robust command, [P] robust robust regression, [R] regress, [R] rreg, also see robust, Huber/White/sandwich estimator of variance robust standard errors, [XT] Glossary robust test for equality of variance, [R] sdtest robust, Abadie–Imbens standard errors, [TE] teffects nnmatch, [TE] teffects psmatch robust, Huber/White/sandwich estimator of variance, [P] robust, [R] vce option, [SVY] variance estimation, [XT] vce options alternative-specific conditional logit model, [R] asclogit multinomial probit regression, [R] asmprobit rank-ordered probit regression, [R] asroprobit ARCH, [TS] arch ARFIMA, [TS] arfima ARIMA and ARMAX, [TS] arima competing-risks regression, [ST] stcrreg complementary log-log regression, [R] cloglog Cox proportional hazards model, [ST] stcox dynamic-factor model, [TS] dfactor fixed-effects models, linear, [XT] xtreg Poisson, [XT] xtpoisson GARCH, [TS] arch generalized linear models, [R] glm for binomial family, [R] binreg generalized method of moments, [R] gmm, [R] ivpoisson heckman selection model, [R] heckman instrumental-variables regression, [R] ivregress interval regression, [R] intreg linear dynamic panel-data estimation, [XT] xtabond, [XT] xtdpd, [XT] xtdpdsys linear regression, [R] regress constrained, [R] cnsreg truncated, [R] truncreg with dummy-variable set, [R] areg logistic regression, [R] logistic, [R] logit, also see logit regression subentry conditional, [R] clogit multinomial, [R] mlogit ordered, [R] ologit rank-ordered, [R] rologit skewed, [R] scobit stereotype, [R] slogit logit regression, [R] logistic, [R] logit, also see logistic regression subentry for grouped data, [R] glogit nested, [R] nlogit maximum likelihood estimation, [R] ml, [R] mlexp multilevel mixed-effects model, [ME] mecloglog, [ME] meglm, [ME] melogit, [ME] menbreg, [ME] meologit, [ME] meoprobit, [ME] mepoisson, [ME] meprobit, [ME] mixed robust, Huber/White/sandwich estimator of variance, continued multinomial logistic regression, [R] mlogit probit regression, [R] mprobit negative binomial regression, [R] nbreg truncated, [R] tnbreg zero-inflated, [R] zinb Newey–West regression, [TS] newey nonlinear least-squares estimation, [R] nl systems of equations, [R] nlsur parametric survival models, [ST] streg Poisson regression, [R] poisson treatment effect, [TE] etpoisson truncated, [R] tpoisson with endogenous regressors, [R] ivpoisson zero-inflated, [R] zip population-averaged models, [XT] xtgee complementary log-log, [XT] xtcloglog logit, [XT] xtlogit negative binomial, [XT] xtnbreg Poisson, [XT] xtpoisson probit, [XT] xtprobit Prais–Winsten and Cochrane–Orcutt regression, [TS] prais probit regression, [R] probit bivariate, [R] biprobit for grouped data, [R] glogit heteroskedastic, [R] hetprobit multinomial, [R] mprobit ordered, [R] heckoprobit, [R] oprobit with endogenous regressors, [R] ivprobit with sample selection, [R] heckprobit quantile regression, [R] qreg random-effects model complementary log-log, [XT] xtcloglog linear, [XT] xtreg logistic, [XT] xtlogit, [XT] xtologit Poisson, [XT] xtpoisson probit, [XT] xtoprobit, [XT] xtprobit state-space model, [TS] sspace structural equation modeling, [SEM] intro 8, [SEM] sem option method( ) summary statistics, mean, [R] mean proportion, [R] proportion ratio, [R] ratio total, [R] total tobit model, [R] tobit with endogenous regressors, [R] ivtobit treatment effect, [TE] etpoisson, [TE] etregress, [TE] teffects aipw, [TE] teffects ipw, [TE] teffects ipwra, [TE] teffects ra
Subject index 85 robust, Huber/White/sandwich estimator of variance, continued truncated negative binomial regression, [R] tnbreg Poisson regression, [R] tpoisson regression, [R] truncreg unobserved-components model, [TS] ucm with endogenous regressors, instrumental-variables regression, [R] ivregress Poisson regression, [R] ivpoisson probit regression, [R] ivprobit tobit regression, [R] ivtobit zero-inflated negative binomial regression, [R] zinb Poisson regression, [R] zip robust, other methods of, [R] rreg, [R] smooth robvar command, [R] sdtest ROC, see receiver operating characteristic analysis roccomp command, [R] roc, [R] roccomp rocfit command, [R] rocfit, [R] rocfit postestimation rocgold command, [R] roc, [R] roccomp rocplot command, [R] rocfit postestimation rocreg command, [R] rocreg, [R] rocreg postestimation, [R] rocregplot rocregplot command, [R] rocregplot roctab command, [R] roc, [R] roctab Rogers and Tanimoto similarity measure, [MV] measure option roh, [R] loneway rolling command, [TS] rolling rolling regression, [TS] rolling, [TS] Glossary rologit command, [R] rologit, [R] rologit postestimation root mean squared error of approximation, [SEM] estat gof, [SEM] example 4, [SEM] methods and formulas for sem rootograms, [G-2] graph other, [R] spikeplot roots of polynomials, [M-5] polyeval( ) rotate command, [MV] factor postestimation, [MV] pca postestimation, [MV] rotate rotate, estat subcommand, [MV] canon postestimation rotatecompare, estat subcommand, [MV] canon postestimation, [MV] factor postestimation, [MV] pca postestimation rotated factor loadings, [MV] factor postestimation principal components, [MV] pca postestimation rotatemat command, [MV] rotatemat rotation, [MV] factor postestimation, [MV] pca postestimation, [MV] rotate, [MV] rotatemat, [MV] Glossary Bentler’s invariant pattern simplicity, see Bentler’s invariant pattern simplicity rotation biquartimax, see biquartimax rotation biquartimin, see biquartimin rotation rotation, continued Comrey’s tandem 1, see Comrey’s tandem 1 and 2 rotations Comrey’s tandem 2, see Comrey’s tandem 1 and 2 rotations covarimin, see covarimin rotation Crawford–Ferguson, see Crawford–Ferguson rotation equamax, see equamax rotation factor parsimony, see factor parsimony rotation minimum entropy, see minimum entropy rotation oblimax, see oblimax rotation oblimin, see oblimin rotation oblique, see oblique rotation orthogonal, see orthogonal rotation parsimax, see parsimax rotation partially specified target, see partially specified target rotation Procrustes, see Procrustes rotation promax, see promax rotation quartimax, see quartimax rotation quartimin, see quartimin rotation toward a target, see toward a target rotation varimax, see varimax rotation round() function, [D] functions, [M-5] trunc( ) rounding rules, [PSS] unbalanced designs roundoff error, [M-5] epsilon( ), [M-5] edittozero( ), [M-5] edittoint( ), [U] 13.11 Precision and problems therein row of matrix, selecting, [M-5] select( ) row operators for data, [D] egen row stripes, [M-6] Glossary roweq macro extended function, [P] macro roweq, matrix subcommand, [P] matrix rownames rowfirst(), egen function, [D] egen rowfullnames macro extended function, [P] macro row-join operator, [M-2] op join rowlast(), egen function, [D] egen row-major order, [M-6] Glossary rowmax() function, [M-5] minmax( ) rowmax(), egen function, [D] egen rowmaxabs() function, [M-5] minmax( ) rowmean(), egen function, [D] egen rowmedian(), egen function, [D] egen rowmin() function, [M-5] minmax( ) rowmin(), egen function, [D] egen rowminmax() function, [M-5] minmax( ) rowmiss(), egen function, [D] egen rowmissing() function, [M-5] missing( ) rownames macro extended function, [P] macro rownames, matrix subcommand, [P] matrix rownames rownonmiss(), egen function, [D] egen rownonmissing() function, [M-5] missing( ) rownumb() function, [D] functions, [P] matrix define rowpctile(), egen function, [D] egen rows() function, [M-5] rows( )
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Subject index Symbols ! (not), see
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Subject index 3 alternative, contin
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Subject index 5 autoregressive, con
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Subject index 7 biquartimax rotatio
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Subject index 9 c(maxstrvarlen) c-c
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Subject index 11 char, continued ma
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Subject index 13 cluster analysis,
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Subject index 15 colnames, matrix s
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Subject index 17 confidence interva
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Subject index 19 convergence, [SEM]
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Subject index 21 cross-sectional da
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Subject index 23 defective matrix,
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Subject index 25 direction of an ef
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Subject index 27 dsign() function,
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Subject index 29 endogenous, contin
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Subject index 31 estat, continued m
Page 33 and 34: Subject index 33 experimental data,
Page 35 and 36: Subject index 35 files, continued c
Page 37 and 38: Subject index 37 frequencies, creat
Page 39 and 40: Subject index 39 ghessenbergd la()
Page 41 and 42: Subject index 41 graphs, continued
Page 43 and 44: Subject index 43 gsem option, conti
Page 45 and 46: Subject index 45 httpproxy, set sub
Page 47 and 48: Subject index 47 incidence-rate rat
Page 49 and 50: Subject index 49 invpoissontail() f
Page 51 and 52: Subject index 51 label values, [P]
Page 53 and 54: Subject index 53 lines, continued l
Page 55 and 56: Subject index 55 lower-triangular m
Page 57 and 58: Subject index 57 matmissing() funct
Page 59 and 60: Subject index 59 means, continued g
Page 61 and 62: Subject index 61 mindices, estat su
Page 63 and 64: Subject index 63 mreldifre() functi
Page 65 and 66: Subject index 65 nbinomialtail() fu
Page 67 and 68: Subject index 67 nonparametric anal
Page 69 and 70: Subject index 69 ocloglog option, s
Page 71 and 72: Subject index 71 outcomes, continue
Page 73 and 74: Subject index 73 pcorr command, [R]
Page 75 and 76: Subject index 75 postestimation com
Page 77 and 78: Subject index 77 probability of a t
Page 79 and 80: Subject index 79 quad precision, [M
Page 81 and 82: Subject index 81 rcap, graph twoway
Page 83: Subject index 83 reset, mi subcomma
Page 87 and 88: Subject index 87 sample size, conti
Page 89 and 90: Subject index 89 sem command, [SEM]
Page 91 and 92: Subject index 91 set, cluster subco
Page 93 and 94: Subject index 93 snapshot, [D] snap
Page 95 and 96: Subject index 95 stability, [TS] va
Page 97 and 98: Subject index 97 stbase command, [S
Page 99 and 100: Subject index 99 Student’s t, dis
Page 101 and 102: Subject index 101 svy: mean command
Page 103 and 104: Subject index 103 tempfile command,
Page 105 and 106: Subject index 105 timer, continued
Page 107 and 108: Subject index 107 Tukey’s Student
Page 109 and 110: Subject index 109 use command, [D]
Page 111 and 112: Subject index 111 verifying data, [
Page 113 and 114: Subject index 113 xtcloglog command
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