Stata Quick Reference and Index

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122 Subject index jackknifed residuals, [R] predict, [R] regress postestimation Jarque–Bera statistic, [TS] varnorm, [TS] vecnorm JCA, [MV] Glossary Jeffreys noninformative prior, [MI] mi impute mvn jitter() option, [G] graph matrix, [G] graph twoway scatter jitterseed() option, [G] graph matrix, [G] graph twoway scatter join operator, [M-2] op join joinby command, [D] joinby, [U] 22 Combining datasets joining datasets, see combining datasets time-span records, [ST] stsplit joint correspondence analysis, [MV] Glossary jumble() function, [M-5] sort( ) jumble() function, [M-5] sort( ) justification of text, [G] textbox options justificationstyle, [G] justificationstyle K Kaiser normalization, [MV] factor postestimation, [MV] pca postestimation, [MV] rotate, [MV] rotatemat Kaiser–Meyer–Olkin sampling adequacy, [MV] factor postestimation, [MV] Glossary, [MV] pca postestimation Kalman filter, [TS] arima, [TS] dfactor, [TS] dfactor postestimation, [TS] Glossary, [TS] sspace [TS] sspace postestimation, forecast, [TS] dfactor postestimation, [TS] sspace postestimation smoothing, [TS] dfactor postestimation, [TS] sspace postestimation kap command, [R] kappa Kaplan–Meier product-limit estimate, [ST] Glossary, [ST] sts [ST] sts generate, [ST] sts graph, [ST] sts list, [ST] sts test, survivor function, [ST] sts; [ST] ltable, [ST] stcox PH-assumption tests kappa command, [R] kappa kapwgt command, [R] kappa kdensity, graph twoway subcommand, [G] graph twoway kdensity kdensity command, [R] kdensity keep command, [D] drop keeping variables or observations, [D] drop Kendall’s tau, [R] spearman, [R] tabulate twoway kernel-density estimator, [R] kdensity smoothing, [G] graph other kernel-weighted local polynomial estimator, [R] lpoly keyboard entry, [U] 10 Keyboard use search, [U] 4 Stata’s help and search facilities keys, [G] legend option Kish design effects, [R] loneway, [SVY] estat Kmatrix() function, [M-5] Kmatrix( ) kmeans, [MV] Glossary kmeans, cluster subcommand, [MV] cluster kmeans and kmedians kmeans clustering, [MV] cluster, [MV] cluster kmeans and kmedians kmedians, [MV] Glossary kmedians, cluster subcommand, [MV] cluster kmeans and kmedians kmedians clustering, [MV] cluster, [MV] cluster kmeans and kmedians kmo, estat subcommand, [MV] factor postestimation, [MV] pca postestimation KNN, [MV] Glossary knn, discrim subcommand, [MV] discrim knn Kolmogorov–Smirnov test, [R] ksmirnov KR-20, [R] alpha Kronecker direct product, [M-2] op kronecker product, [D] cross, [P] matrix define Kruskal stress, [MV] Glossary, [MV] mds postestimation Kruskal–Wallis test, [R] kwallis ksmirnov command, [R] ksmirnov ktau command, [R] spearman kth-nearest neighbor, [MV] discrim knn, [MV] Glossary Kuder–Richardson Formula 20, [R] alpha Kulczynski coefficient similarity measure, [MV] measure option kurt(), egen function, [D] egen kurtosis, [MV] mvtest normality, [R] lv, [R] regress postestimation, [R] sktest, [R] summarize, [R] tabstat, [TS] varnorm, [TS] vecnorm kwallis command, [R] kwallis L L1-norm models, [R] qreg l1title() option, [G] title options l2title() option, [G] title options label, snapshot subcommand, [D] snapshot label copy command, [D] label command, [U] 12.6 Dataset, variable, and value labels data command, [D] label define command, [D] label dir command, [D] label drop command, [D] label language command, [D] label language list command, [D] label macro extended function, [P] macro save command, [D] label values command, [D] label variable command, [D] label
Subject index 123 label values, [P] macro, [U] 12.6 Dataset, variable, and value labels; [U] 13.10 Label values labelbook command, [D] labelbook labeling data, [U] 12.6 Dataset, variable, and value labels; [D] describe, [D] label, [D] label language, [D] notes in other languages, [U] 12.6.4 Labels in other languages labels, axis, [G] axis label options creating, [D] varmanage editing, [D] varmanage marker, [G] marker label options LAD regression, [R] qreg ladder command, [R] ladder ladder-of-powers plots, [G] graph other, [R] ladder lag-exclusion statistics, [TS] varwle lag operator, [TS] Glossary, [U] 11.4.4 Time-series varlists lag-order selection statistics, [TS] varsoc; [TS] var, [TS] var intro, [TS] var svar, [TS] vec intro lagged values, [U] 13.7 Explicit subscripting, [U] 13.9.1 Generating lags, leads, and differences Lagrange-multiplier test, [R] regress postestimation time series, [TS] varlmar, [TS] veclmar Lance and Williams’ formula, [MV] cluster language syntax, [P] syntax, [U] 11 Language syntax languages, multiple, [D] label language LAPACK, [M-1] LAPACK, [M-5] cholesky( ), [M-5] cholinv( ), [M-5] cholsolve( ), [M-5] eigensystem( ), [M-5] eigensystemselect( ), [M-5] fullsvd( ), [M-5] ghessenbergd( ), [M-5] lapack( ), [M-5] lud( ), [M-5] luinv( ), [M-5] lusolve( ), [M-5] qrd( ), [M-5] qrinv( ), [M-5] qrsolve( ), [M-5] svd( ), [M-5] svsolve( ), [M-6] Glossary latent roots, [M-5] eigensystem( ) Latin-square designs, [MV] manova, [R] anova, [R] pkshape launch dialog box, [R] db LAV regression, [R] qreg Lawley–Hotelling trace statistic, [MV] canon, [MV] Glossary, [MV] manova, [MV] mvtest means lceffects, estat subcommand, [SVY] estat lcolor() option, [G] connect options, [G] rspike options LDA, [MV] discrim lda, [MV] Glossary lda, discrim subcommand, [MV] discrim lda lead operator, [U] 11.4.4 Time-series varlists values, see lagged values leap seconds, [TS] tsset least absolute deviations, [R] qreg residuals, [R] qreg value regression, [R] qreg least squared deviations, [R] regress, [R] regress postestimation; [R] areg, [R] cnsreg, [R] nl least squares, see linear regression generalized, see FGLS least-squares means, [R] margins [U] 20.14.1 Obtaining expected marginal means left eigenvectors, [M-5] eigensystem( ) left suboption, [G] justificationstyle lefteigensystem() function, [M-5] eigensystem( ) lefteigensystem() function, [M-5] eigensystem( ) lefteigensystemselect*() functions, [M-5] eigensystemselect( ) leftgeigensystem() function, [M-5] geigensystem( ) leftgeigensystemselect*() function, [M-5] geigensystem( ) legend() option, [G] legend option legends, [G] legend option problems, [G] legend option use with by(), [G] by option, [G] legend option legendstyle, [G] legendstyle length, [M-5] abs( ), [M-5] rows( ), [M-5] strlen( ) length() function, [D] functions, [M-5] rows( ) length macro extended function, [P] macro length of string function, [D] functions less than (or equal) operator, [U] 13.2.3 Relational operators letter values, [R] lv level, set subcommand, [R] level, [R] set level command and value, [P] macro levels, [U] 11.4.3 Factor variables levelsof command, [P] levelsof Levene’s robust test statistic, [R] sdtest leverage, [R] logistic postestimation, [R] predict, [R] regress postestimation obtaining with weighted data, [R] predict leverage plots, [G] graph other leverage-versus-(squared)-residual plot, [R] regress postestimation Levin–Lin–Chu test, [XT] xtunitroot lexis command, [ST] stsplit lexis diagram, [ST] stsplit lfit, graph twoway subcommand, [G] graph twoway lfit lfitci, graph twoway subcommand, [G] graph twoway lfitci libraries, [M-1] how, [M-3] mata mlib, [M-3] mata which license, [R] about life tables, [ST] Glossary, [ST] ltable likelihood, see maximum likelihood estimation likelihood displacement value, [ST] Glossary, [ST] stcox postestimation likelihood-ratio chi-squared of association, [R] tabulate twoway test, [R] lrtest, [U] 20.11.3 Likelihood-ratio tests Likert summative scales, [R] alpha
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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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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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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.
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Author index 65 Conover, W. J., [R]
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Author index 67 Feinleib, M., [XT]
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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 and 120: Subject index 115 graph, continued
Page 121 and 122: Subject index 117 Harrell’s C, [S
Page 123 and 124: Subject index 119 Im-Pesaran-Shin t
Page 125: Subject index 121 invfft() function
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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