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📄 stata12.key

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.e STB-30 @net:stb 30 dm41!dm41@
.c stb
.t Online documentation for _result() contents
.a J. R. Gleason
.o @_result@ if installed
.k prog-ramming prog-rams display sav-ed result-s debug disp_res disp_s disp
.k s_-# _res-ult data-sets set-s manage-ment _res5dcn _res5dds
.k _res5din _res5s1w _res5scr
.k _res5sfa _res5sqr _res5srg _res5srr _res5sta _res5sts _res5sum _res6avr
.k _res6mac _res6mlo _res7max _res_all _res_idx
.z
.x
	3/96	pp.3--5; STB Reprints Vol 5, pp.49--52
	the contents of Saved Results is available online;
	Saved Results were changed in Stata 6

.e STB-30 @net:stb 30 ip8.1!ip8.1@
.c stb
.t An even more enhanced for command
.a P. Royston
.o @for3@ if installed
.k util-ity repeat command-s var-iables edit correct modify for-3
.z
.x
	3/96	pp.5--6; STB Reprints Vol 5, pp.65--66
	incorporated into improved @for@ command in Stata 5.0

.e STB-30 @net:stb 30 sg50!sg50@
.c stb
.t Graphical assessment of linear trend
.a J. M. Garrett
.o @lintrend@ if installed
.k stat-istics trend linear dicho-tomous lintrend
.k plot-s plot-ting graph-s graph-ing pred-ictions pred-icted value-s graph-ics
.k model-s reg-ressions logis-tic logit log odds bina-ry outcome-s
.x
	3/96	pp.9-15; STB Reprints Vol 5, pp.152--160
	graphically examines the relationship between the log odds
	of a binary outcome by categories of an ordinal or interval
	independent variable

.e STB-30 @net:stb 30 sg49!sg49@
.c stb
.t An improved command for paired t tests
.a J. R. Gleason
.o @rmttest@ if installed
.k equal-ity test-s test-ing mean-s ave-rages distrib-utions rmttest
.k hyp-othesis hyp-otheses stud-entst t-tests match-ed pair-s stat-istics
.k pair-ed repeated meas-urements
.x
	3/96	pp.6--9; STB Reprints Vol 5, pp.147--152
	performs repeated measures (or matched-pairs) t test when
	pairs y1 and y2 are stored as values of a single response
	variable y

.e STB-30 @net:stb 30 snp10!snp10@
.c stb
.t Nonparametric regression:  Kernel, WARP and K-NN estimators
.a Salgado-Ugarte, Shimizu, Taniuchi
.k kern-el dens-ity est-imators est-imation stat-istics est-imates
.k smooth-ers smooth-ing hist-ograms nonpar-ametric non param-etric
.k warp-ing univar-iate distrib-utions reg-ressions kernreg warpreg gwarpreg
.k band-width width bands bin-s interv-als knnreg
.o @kernreg@, @knnreg@ if installed
.x
	3/96	pp.15-30; STB Reprints Vol 5, pp.197--218
	performs kernel regression

.e STB-29 crc43
.c stb
.t Test nonlinear hypotheses after model estimation
.k equal-ity test-s coef-ficients model-s est-imation hyp-othesis hyp-otheses
.k chi-squared sq-uared chi-2 2 f-statistics stat-istics testparm
.k reg-ressions ml-e max-imum like-lihood contrast-s beta param-eters
.k cov-ariances constrain-ts est-imates nonlin-ear non linear wald test-ing
.o @testnl@
.z
.x
	1/96	pp.2--4; STB Reprints Vol 5, pp.15--18
	incorporated into Stata 5.0

.e STB-29 @net:stb 29 dm40!dm40@
.c stb
.t Converting string variables to numeric variables
.a R. M. Farmer
.o @conv2num@ if installed
.k data-sets set-s manage-ment conv2num var-iables str-ings num-eric convert real
.z
.x
	1/96	pp.8-9; STB Reprints Vol 5, pp.48--49
	@destring@ available in Stata 7.0

.e STB-29 dm39
.c stb
.t Using .hlp files to document data analysis
.a M. Hills
.k data-sets set-s manage-ment docu-ment help anal-ysis descrip-tion
.x
	1/96	p.8; STB Reprints Vol 5, pp.47--48		 (no commands)
	description of how one might use ^.hlp^ files to document
	data analysis

.e STB-29 @net:stb 29 dm38!dm38@
.c stb
.t A more automated merge procedure
.a R. M. Farmer
.o @mergein@ if installed
.k comb-ine data-sets set-s join merge var-iables add mergein manage-ment
.z
.x
	1/96	pp.6--7; STB Reprints Vol 5, pp.45--47
	automates merge process by guaranteeing that datasets are sorted
	and that neither contains ^_merge^ variable; also permits matching
	variables to have different names in the datasets

.e STB-29 @net:stb 29 dm37!dm37@
.c stb
.t Extended merge capabilities
.a J. Faust
.o @xmerge@ if installed
.k comb-ine data-sets set-s join merge var-iables add xmerge-d dict-ionary
.k manage-ment
.x
	1/96	pp.5--6; STB Reprints Vol 5, pp.43--45
	merge two or more datasets or two or more dictionary files

.e STB-29 @net:stb 29 dm27.1!dm27.1@
.c stb
.t Correction to improved collapse
.a W. Gould
.o @coll2@ if installed
.k aggregate stat-istics mean-s med-ians stand-ard dev-iations std sum-s
.k nonmiss-ing obs-ervations max-imums max-ima min-imums min-ima percent-iles
.k interquart-ile range set-s data-sets ave-rages centile-s creat-e make
.k count-s quantile-s non miss-ing freq-uencies freq-uency iqr quartile-s
.k func-tions contain-ing variance-s proc summ-ary collapse weight-s coll2
.k manage-ment total-s
.z
.x
	1/96	p.4; STB Reprints Vol 5, p.19
	improvements incorporated into improved @collapse@ command
	in Stata 5.0

.e STB-29 @net:stb 29 gr19!gr19@
.c stb
.t Misleading or confusing boxplots
.a J. C. Nash
.k graph-ics graph-s plot-s box-plots miss-ing value-s scaled unscaled data
.x
	1/96	pp.14--17; STB Reprints Vol 5, pp.60--64
	discussion of how scaling of data and/or missing values may
	lead to misleading boxplots

.e STB-29 @net:stb 29 gr18!gr18@
.c stb
.t Graphing high-dimensional data using parallel coordinates
.a J. R. Gleason
.o @parcoord@ if installed
.k graph-ics graph-s parcoord coor-dinates paral-lel plot-s high dimen-sional
.k parc multiv-ariate data
.x
	1/96	pp.10--14; STB Reprints Vol 5, pp.53--60
	produce ParC plots (parallel coordinate plots), a method for
	representing multivariate data

.e STB-29 @net:stb 29 ip12!ip12@
.c stb
.t Parsing tokens in Stata
.a S. Becketti
.o @xparse@, @readtok@ if installed
.k prog-ramming prog-rams pars-e macro-s arg-uments user input-ting input-ing
.k xparse readtok
.z
.x
	1/96	pp.19--21; STB Reprints Vol 5, pp.73--76
	programs that extend Stata's low-level parsing capabilities

.e STB-29 @net:stb 29 ip11!ip11@
.c stb
.t A tool for manipulating s_# objects
.a J. R. Gleason
.o @s_no@ if installed
.k s_-no prog-ramming prog-rams util-ity s_-#
.z
.x
	1/96	pp.17--19; STB Reprints Vol 5, pp.71--73
	programming tool; display or erase macros, scalars, or
	matrices with names of the form S_#

.e STB-29 @net:stb 29 sg48!sg48@
.c stb
.t Predictions in the original metric for log-transformed models
.a R. Goldstein
.o @predlog@ if installed
.k predlog stat-istics pred-ictions transfo-rmations transfo-rmed log
.k retransfo-rmations smear-ing est-imates duan exp-onentiation
.x
	1/96	pp.27--29; STB Reprints Vol 5, pp.145--147
	calculates three different retransformations, which allow
	obtaining predictions in the original metric

.e STB-29 @net:stb 29 sg47!sg47@
.c stb
.t A plot and a test for the chi-squared distribution
.a P. Royston
.o @qchi@, @a2@ if installed
.k qqplot qchi a2 anderson-darling darling goodness fit prob-ability plot-s
.k norm-ality chi-squared square-d q-q quantile-s distrib-utions stat-istics
.k unif-orm
.x
	1/96	pp.26--27; STB Reprints Vol 5, pp.142--144
	produces a q-q plot for the chi-squared distribution; another
	command performs Anderson-Darling goodness-of-fit test for
	normal, uniform, and chi-squared distributions;
	incorporated into Stata 5

.e STB-29 @net:stb 29 sg46!sg46@
.c stb
.t Huber correction for two-stage least squares estimates
.a M. Over, D. Jolliffe, A. Foster
.o @hreg2sls@ if installed
.k huber reg-ressions prob-ability weight-ing weight-s white-s meth-od
.k stand-ard err-ors std est-imates clus-tering weight-ed hreg hreg2sls iv
.k instrum-ental var-iables least sq-uares sq-uared two-stage stage 2sls tsls
.z
.x
	1/96	pp.24--25; STB Reprints Vol 5, pp.140--142
	predecessor of robust estimator of variance introduced
	in Stata 5.0; see help @regress@

.e STB-29 @net:stb 29 sg29.1!sg29.1@
.c stb
.t Tabulation of observed/expected ratios & conf. intervals
.a P. Sasieni
.o @smrby@ if installed
.k mortality smr stand-ardized stand-ardised tab-ulations tab-ulate ratio-s
.k conf-idence interv-als stat-istics smrby
.x
	1/96	pp.21--24; STB Reprints Vol 5, pp.87--90
	improved version of ^smr^

.e STB-29 @net:stb 29 snp9!snp9@
.c stb
.t Kornbrot's rank difference test
.a R. Goldstein
.o @kornbrot@ if installed
.k equal-ity distrib-utions pop-ulations hyp-othesis hyp-otheses
.k match-ed pair-s test-s test-ing signrank data
.k nonpar-ametric rank-sums sum-s order non param-etric kornbrot ordinal
.k wilcox-on sign-edranks sign-ed two samp-les stat-istics
.x
	1/96	pp.29--31; STB Reprints Vol 5, pp.195--197
	alternative to @signrank@ that is useful when one has ordinal data

.e STB-28 crc42
.c stb
.t Improvements to the heckman command
.k linear reg-ressions est-imation heckman selec-tion model-s mill-s ratio-s
.k multiv-ariate partici-pation stat-istics est-imates ml-e bias
.k max-imum like-lihood
.o @heckman@
.z
.x
	11/95	pp.6--7; STB Reprints Vol 5, pp.13--15
	incorporated into Stata 5.0

.e STB-28 crc41
.c stb
.t New lfit, lroc, and lstat commands
.k lfit lroc lstat lsens stat-istics logis-tic reg-ressions
.k dicho-tomous bina-ry outcome-s model-s lpredict
.k est-imation ml-e max-imum like-lihood step-wise logit
.o @lfit@
.z
.x
	11/95	pp.2--6; STB Reprints Vol 5, pp.8--13
	incorporated into Stata 5.0

.e STB-28 @net:stb 28 dm36!dm36@
.c stb
.t Comparing two Stata datasets
.a J. R. Gleason
.o @compdta@ if installed
.k compdta compar-e file-s two compar-isons data-sets set-s manage-ment
.z
.x
	11/95	pp.10--13; STB Reprints Vol 5, pp.39--43
	compare the varlist from the dataset in memory with like-named
	variables in the Stata-format dataset on disk; alternative to
	@cf@ command

.e STB-28 @net:stb 28 dm35!dm35@
.c stb
.t A utility for surveying Stata-format datasets
.a T. J. Schmidt
.o @dtainfo@ if installed
.k dtainfo display content-s data-sets set-s var-iables descrip-tion
.k describe miss-ing value-s stor-age type-s manage-ment
.z
.x
	11/95	pp.7--9; STB Reprints Vol 5, pp.36--39
	utility program that reports information about the contents of
	Stata-format datasets; program not available for Macintosh

.e STB-28 @net:stb 28 ip10!ip10@
.c stb
.t Finding an observation number
.a S. Becketti
.o @findobs@ if installed
.k findobs prog-ramming prog-rams util-ity
.x
	11/95	pp.13--14; STB Reprints Vol 5, pp.70--71
	display the observation number of the i-th observation that
	satisfies specified conditions; useful to programmers

.e STB-28 sbe12
.c stb
.t Using lfit and lroc to evaluate mortality prediction models
.a J. M. Tilford, P. K. Roberson, and D. H. Fiser
.k lfit lroc stat-istics mortality roc logis-tic logit pred-ictions
.k calibra-tion discrimination prism
.x
	11/95	pp.14--18; STB Reprints Vol 5, pp.77--81	 (no commands)
	discussion of how the new @lfit@ and @lroc@ commands (see crc41)
	can be used to evaluate mortality prediction models

.e STB-28 @net:stb 28 sg45!sg45@
.c stb
.t Maximum-likelihood ridge regression
.a R. L. Obenchain
.o @rxridge@, @rxrisk@, @rxrcrlq@, @rxrsimu@ if installed
.k rxrcrlq rxridge rxrmaxl rxrrisk rxrsimu stat-istics max-imum like-lihood
.k reg-ressions est-imation ridge rxrmkdta
.z
.x
	11/95	pp.22--35; STB Reprints Vol 5, pp.121--140
	overview of ridge regression concepts along with programs
	to monitor the effects of shrinkage

.e STB-28 @net:stb 28 sg44!sg44@
.c stb
.t Random number generators
.a J. Hilbe and W. Linde-Zwirble
.o @rnd@ if installed
.k rnd rand-om num-bers gen-erate gen-erators unif-orm norm-al student-s t
.k chi-squared square-d f poisson binom-ial gamma exp-onential weibull beta
.k rndbb rndbin rndbinx rndchi rndexp rndf rndgam rndgamx rndivg rndivgx
.k rndlgn rndpoi rndpoix rndt rndwei log-normal
.x
	11/95	pp.20--21; STB Reprints Vol 5, pp.118--121
	programs to implement random number generators that allows user
	to generate synthetic data from a variety of distributions

.e STB-28 @net:stb 28 sg43!sg43@
.c stb
.t Modified t statistics
.a R. Goldstein
.o @modt@, @obrien@ if installed
.k modt modti obrien stat-istics equal-ity test-s test-ing mean-s ave-rages
.k distrib-utions hyp-othesis hyp-otheses immed-iate stud-entst t-tests
.k match-ed pair-s pair-ed unpair-ed stat-istics
.x
	11/95	pp.18--19; STB Reprints Vol 5, pp.117--118
	alternative commands to @ttest@ and @ranksum@ for use when data is
	skewed, when the groups have unequal variance, or when there is
	heterogeneity of effect

.e STB-27 @net:stb 27 ip9!ip9@
.c stb
.t Repeat Stata command by variable(s)
.a P. Royston
.k lang-uage synt-ax repeat command-s by group-s each byvar
.o @byvar@ if installed
.z
.x
	9/95	pp.3--5; STB Reprints Vol 5, pp.67--69
	ado commands byable in Stata 7.0

.e STB-27 @net:stb 27 snp6.2!snp6.2@
.c stb
.t Rules for bandwidth selection in univariate density estimation
.a Salgado-Ugarte, Shimizu, Taniuchi
.k univar-iate band-width width bands bin-s interv-als
.k hist-ograms kern-el bandw l2cvwarp bcvwarp kerneld warpden-s
.k kern-el dens-ity est-imators est-imation stat-istics est-imates
.k smooth-ers smooth-ing hist-ograms nonpar-ametric non param-etric
.k warp-ing univar-iate distrib-utions wardens
.o @bandw@, @warpden@ if installed
.z
.x
	9/95	pp.5--19; STB Reprints Vol 5, pp.172--190
	surveys a variety of methods for selecting bandwidth for
	univariate density estimation; programs presented for
	determining reference values for bandwidth

.e STB-27 @net:stb 27 ssa8!ssa8@

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