Stata Quick Reference and Index

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116 Subject index graphs, continued impulse–response functions, [TS] irf, [TS] irf cgraph, [TS] irf graph, [TS] irf ograph integrals, [R] dydx ladder-of-power histograms, [R] ladder leverage-versus-(squared)-residual, [R] regress postestimation loading after candisc, [MV] scoreplot after discrim lda, [MV] scoreplot after factor, [MV] scoreplot after pca, [MV] scoreplot logistic diagnostic, [R] logistic postestimation lowess smoothing, [R] lowess MDS configuration, [MV] mds postestimation means and medians, [R] grmeanby normal probability, [R] diagnostic plots overall look of, [G] schemes intro parameterized curves, [D] range partial correlogram, [TS] corrgram partial residual, [R] regress postestimation partial-regression leverage, [R] regress postestimation periodogram, [TS] pergram procrustes overlay, [MV] procrustes postestimation quality control, [R] qc quantile, [R] diagnostic plots quantile–normal, [R] diagnostic plots quantile–quantile, [R] diagnostic plots regression diagnostic, [R] regress postestimation residual versus fitted, [R] regress postestimation residual versus predictor, [R] regress postestimation ROC curve, [R] logistic postestimation, [R] roc, [R] rocfit postestimation rootograms, [R] spikeplot saving, [G] graph save, [G] saving option score after candisc, [MV] scoreplot after discrim lda, [MV] scoreplot after factor, [MV] scoreplot after pca, [MV] scoreplot Shepard diagram, [MV] mds postestimation smoothing, [R] kdensity, [R] lowess, [R] lpoly spike plot, [R] spikeplot stem-and-leaf, [R] stem sunflower, [R] sunflower suppressing, [G] nodraw option symmetry, [R] diagnostic plots time-versus-concentration curve, [R] pk, [R] pkexamine white-noise test, [TS] wntestb grdistances, estat subcommand, [MV] discrim lda postestimation, [MV] discrim qda postestimation greater than (or equal) operator, [U] 13.2.3 Relational operators .grec files, [U] 11.6 File-naming conventions Greek letters, [G] text Greenhouse–Geisser epsilon, [R] anova Greenwood confidence intervals, [ST] sts grid definition, [G] gridstyle lines, [G] axis label options without ticks, [G] tickstyle gridstyle, [G] gridstyle grmeanby command, [R] grmeanby grmeans, estat subcommand, [MV] discrim lda postestimation group(), egen function, [D] egen group, estat subcommand, [XT] xtmelogit postestimation, [XT] xtmepoisson postestimation, [XT] xtmixed postestimation group-data regression, [R] glogit, [R] intreg grouping variables, generating, [MV] cluster generate groups, graphs by, [G] by option grsummarize, estat subcommand, [MV] discrim estat, [MV] discrim knn postestimation, [MV] discrim lda postestimation, [MV] discrim logistic postestimation, [MV] discrim qda postestimation gs1 print color mapping, [G] set printcolor gs2 print color mapping, [G] set printcolor gs3 print color mapping, [G] set printcolor gschurd() function, [M-5] gschurd( ) gschurd() function, [M-5] gschurd( ) gschurdgroupby() function, [M-5] gschurd( ) gschurdgroupby() function, [M-5] gschurd( ) gschurdgroupby la() function, [M-5] gschurd( ) gschurd la() function, [M-5] gschurd( ) gsort command, [D] gsort GUI, examples of, [U] 2 A brief description of Stata GUI programming, [P] dialog programming H hadamard() matrix function, [D] functions, [P] matrix define Hadamard matrix, [SVY] Glossary, [SVY] svy brr hadri, xtunitroot subcommand, [XT] xtunitroot Hadri Lagrange multiplier stationarity test, [XT] xtunitroot half option, [G] graph matrix half-normal model, stochastic frontier, [R] frontier halfyear() function, [D] dates and times, [D] functions, [M-5] date( ) halfyearly() function, [D] dates and times, [D] functions, [M-5] date( ) halton() function, [M-5] halton( ) halton() function, [M-5] halton( ) Halton set, [M-5] halton( ) Hamann coefficient similarity measure, [MV] measure option Hammersley set, [M-5] halton( ) hard missing value, [MI] Glossary harmonic mean, [R] ameans
Subject index 117 Harrell’s C, [ST] stcox postestimation Harris–Tzavalis test, [XT] xtunitroot has eprop() function, [D] functions hash functions, [M-5] hash1( ) hash tables, [M-5] asarray( ) hash1() function, [M-5] hash1( ) hasmissing() function, [M-5] missing( ) hat matrix, see projection matrix, diagonal elements of hausman command, [R] hausman Hausman specification test, [R] hausman, [XT] xtreg postestimation Hausman–Taylor estimator, [XT] xthtaylor postestimation, [XT] xthtaylor postestimation Haver Analytics, [TS] haver haver command, [D] infile, [TS] haver hazard constributions, [ST] Glossary function, [G] graph other, [ST] sts, [ST] sts generate, [ST] sts list graph of, [ST] ltable, [ST] stcurve, [ST] sts graph ratio, [ST] Glossary minimal detectable difference, [ST] stpower minimal effect size, [ST] stpower hazard tables, [ST] ltable hbar, graph subcommand, [G] graph bar hbox, graph subcommand, [G] graph box headlabel option, [G] graph twoway pccapsym, [G] graph twoway pcscatter health ratios, [R] binreg heart attack data, [MI] intro substantive, [MI] mi estimate, [MI] mi impute logit, [MI] mi impute mlogit, [MI] mi impute monotone, [MI] mi impute mvn, [MI] mi impute ologit, [MI] mi impute pmm, [MI] mi impute regress heckman command, [R] heckman, [R] heckman postestimation, also see postestimation command Heckman selection model, [R] heckman, [R] heckprob, [SVY] svy estimation heckprob command, [R] heckprob, [R] heckprob postestimation, also see postestimation command height() textbox option, [G] added text options help, [M-1] help, [M-3] mata help help, view subcommand, [R] view help command, [R] help, [U] 4 Stata’s help and search facilities, [U] 7 –more– conditions writing your own, [U] 18.11.6 Writing online help help file search, [R] hsearch help — I don’t know what to do, [U] 3 Resources for learning and using Stata help system, searching, [R] hsearch help d, view subcommand, [R] view Henze–Zirkler normality test, [MV] mvtest normality Hermitian adjoin, [M-2] op transpose, [M-5] conj( ) matrices, [M-5] issymmetric( ), [M-5] makesymmetric( ), [M-6] Glossary Hermitian, continued transpose, [M-2] op transpose, [M-5] conj( ) Hessenberg decomposition, [M-5] hessenbergd( ), [M-6] Glossary form, [M-6] Glossary hessenbergd() function, [M-5] hessenbergd( ) hessenbergd() function, [M-5] hessenbergd( ) hessenbergd la() function, [M-5] hessenbergd( ) hessian option, [R] maximize heterogeneity test, [ST] epitab heteroskedastic probit model, [SVY] svy estimation regression, [R] hetprob heteroskedasticity, [XT] xtgls conditional, [R] regress postestimation time series, [TS] arch multiplicative heteroskedastic regression, [TS] arch robust variances, see robust, Huber/White/sandwich estimator of variance stochastic frontier, [R] frontier test for, [R] regress postestimation, [R] regress postestimation time series hetprob command, [R] hetprob, [R] hetprob postestimation, also see postestimation command hettest, estat subcommand, [R] regress postestimation hexadecimal report, [D] hexdump hexdump command, [D] hexdump Heywood case, [MV] Glossary Heywood solution, [MV] Glossary hh() function, [D] dates and times, [D] functions, [M-5] date( ) hhC() function, [D] dates and times, [D] functions, [M-5] date( ) hierarchical cluster analysis, [MV] cluster, [MV] cluster linkage, [MV] clustermat clustering, [MV] Glossary clustering methods, [MV] Glossary model, [XT] Glossary, [XT] xtmelogit, [XT] xtmepoisson, [XT] xtmixed regression, [R] areg, [R] nestreg samples, [R] anova, [R] loneway; [R] areg high-low charts, [G] graph twoway rbar, [G] graph twoway rcap, [G] graph twoway rspike Hilbert() function, [M-5] Hilbert( ) Hildreth–Lu regression, [TS] prais HILO, [M-5] byteorder( ) histogram, graph twoway subcommand, [G] graph twoway histogram histogram command, [R] histogram histograms, [G] graph twoway histogram, [R] histogram dotplots, [R] dotplot kernel density estimator, [R] kdensity ladder-of-powers, [R] ladder
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STATA QUICK REFERENCE AND INDEX REL
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i Table of contents Combined subjec
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2 Inputting and saving data [GS] Ch
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4 [D] changeeol . . . . . . . . . .
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6 [R] estimates title . . . . . . .
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8 [G] graph twoway lowess . . . . .
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10 Graph schemes [G] schemes intro
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12 [MV] clustermat . . . . . . . .
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14 [MV] scoreplot . . . . . . . . .
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16 [R] mprobit . . . . . . . . . .
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18 Nonparametric statistics [R] kde
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20 [R] predict . . . . . . . . . .
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22 [TS] tsreport . . . . . . . . .
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24 [P] fvexpand . . . . . . . . . .
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26 Mata [M] Mata Reference Manual .
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Title estimation commands — Quick
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30 estimation commands — Quick re
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Page 40 and 41:
Title format — Quick reference fo
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Title missing values — Quick refe
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40 postestimation commands — Quic
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Page 52 and 53:
Title prefix commands — Quick ref
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Title reading data — Quick refere
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Title Acronym glossary 2SIV 2SLS 3S
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Acronym glossary 55 IC ICD-9 IIA i.
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Acronym glossary 57 QDA QML rc RCT
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Vignettes index 59 Vignettes index
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Author index 61 Author index A Aale
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Author index 63 Blackburne III, E.
Page 69 and 70: Author index 65 Conover, W. J., [R]
Page 71 and 72: Author index 67 Feinleib, M., [XT]
Page 73 and 74: Author index 69 Green, P. E., [MV]
Page 75 and 76: Author index 71 Hipel, K. W., [TS]
Page 77 and 78: Author index 73 Klein, J. P., [ST]
Page 79 and 80: Author index 75 Lu, J. Y., [TS] pra
Page 81 and 82: Author index 77 Muirhead, R. J., [M
Page 83 and 84: Author index 79 Ponce de Leon, A.,
Page 85 and 86: Author index 81 Schonlau, M., [R] g
Page 87 and 88: Author index 83 ter Bogt, T., [MV]
Page 89 and 90: Author index 85 Wichern, D. W., con
Page 91 and 92: Subject index 87 Subject index ! (n
Page 93 and 94: Subject index 89 args command, [P]
Page 95 and 96: Subject index 91 bias corrected and
Page 97 and 98: Subject index 93 c(minbyte) c-class
Page 99 and 100: Subject index 95 choice models, con
Page 101 and 102: Subject index 97 cointegration, con
Page 103 and 104: Subject index 99 constrained estima
Page 105 and 106: Subject index 101 cumsp command, [T
Page 107 and 108: Subject index 103 describe, continu
Page 109 and 110: Subject index 105 DLL, [P] plugin D
Page 111 and 112: Subject index 107 end-of-line chara
Page 113 and 114: Subject index 109 estat, continued
Page 115 and 116: Subject index 111 FEVD, [TS] Glossa
Page 117 and 118: Subject index 113 fsave, window sub
Page 119: Subject index 115 graph, continued
Page 123 and 124: Subject index 119 Im-Pesaran-Shin t
Page 125 and 126: Subject index 121 invfft() function
Page 127 and 128: Subject index 123 label values, [P]
Page 129 and 130: Subject index 125 loading, [MV] Glo
Page 131 and 132: Subject index 127 markers, [G] mark
Page 133 and 134: Subject index 129 mband, graph twow
Page 135 and 136: Subject index 131 missing data, [MI
Page 137 and 138: Subject index 133 mvdecode command,
Page 139 and 140: Subject index 135 number to string
Page 141 and 142: Subject index 137 parameter trace f
Page 143 and 144: Subject index 139 polytomous logist
Page 145 and 146: Subject index 141 proportions, [R]
Page 147 and 148: Subject index 143 rc built-in varia
Page 149 and 150: Subject index 145 return, [M-2] ret
Page 151 and 152: Subject index 147 RVI, see relative
Page 153 and 154: Subject index 149 set, continued fa
Page 155 and 156: Subject index 151 Sneath and Sokel
Page 157 and 158: Subject index 153 Stata, continued
Page 159 and 160: Subject index 155 stset command for
Page 161 and 162: Subject index 157 svy: truncreg com
Page 163 and 164: Subject index 159 tests, continued
Page 165 and 166: Subject index 161 truncating real n
Page 167 and 168: Subject index 163 variables, contin
Page 169 and 170: Subject index 165 weights, continue
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