Subject index - Stata
Subject index - Stata
Subject index - Stata
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<strong>Subject</strong> <strong>index</strong> 17<br />
confidence interval, continued<br />
for tabulated proportions, [SVY] svy: tabulate<br />
twoway<br />
for totals, [R] total<br />
linear combinations, [SVY] svy postestimation<br />
set default, [R] level<br />
confidence levels, [R] level<br />
config, estat subcommand, [MV] mds<br />
postestimation<br />
configuration, [MV] Glossary<br />
configuration plot, [MV] mds postestimation plots,<br />
[MV] Glossary<br />
confirm<br />
existence command, [P] confirm<br />
file command, [P] confirm<br />
format command, [P] confirm<br />
matrix command, [P] confirm<br />
names command, [P] confirm<br />
number command, [P] confirm<br />
scalar command, [P] confirm<br />
variable command, [P] confirm<br />
confirm, datasignature subcommand,<br />
[D] datasignature<br />
confirmatory factor analysis, [MV] intro,<br />
[SEM] intro 5, [SEM] example 15,<br />
[SEM] example 30g, [SEM] Glossary<br />
conformability, [M-2] void, [M-6] Glossary, also see<br />
c-conformability, also see p-conformability, also<br />
see r-conformability<br />
confounding, [ST] Glossary<br />
confusion matrix, [MV] Glossary<br />
conj() function, [M-5] conj( )<br />
conj() function, [M-5] conj( )<br />
conjoint analysis, [R] rologit<br />
conjugate, [M-5] conj( ), [M-6] Glossary<br />
conjugate transpose, [M-2] op transpose, [M-5] conj( ),<br />
[M-6] Glossary<br />
connect() option, [G-3] cline options,<br />
[G-3] connect options, [G-4] connectstyle<br />
connected, graph twoway subcommand, [G-2] graph<br />
twoway connected<br />
connectstyle, [G-4] connectstyle<br />
conren, set subcommand, [R] set<br />
console,<br />
controlling scrolling of output, [P] more, [R] more<br />
obtaining input from, [P] display<br />
constant conditional-correlation model, [TS] mgarch,<br />
[TS] mgarch ccc<br />
constrained estimation, [R] constraint, [R] estimation<br />
options<br />
alternative-specific<br />
conditional logistic model, [R] asclogit<br />
multinomial probit regression, [R] asmprobit<br />
rank-ordered probit regression, [R] asroprobit<br />
ARCH, [TS] arch<br />
ARFIMA, [TS] arfima<br />
ARIMA and ARMAX, [TS] arima<br />
competing risks, [ST] stcrreg<br />
constrained estimation, continued<br />
complementary log-log regression, [R] cloglog<br />
dynamic factor model, [TS] dfactor<br />
fixed-effects models<br />
logit, [XT] xtlogit<br />
negative binomial, [XT] xtnbreg<br />
Poisson, [XT] xtpoisson<br />
GARCH model, [TS] mgarch ccc, [TS] mgarch<br />
dcc, [TS] mgarch dvech, [TS] mgarch vcc<br />
generalized linear models, [R] glm<br />
for binomial family, [R] binreg<br />
generalized negative binomial regression, [R] nbreg<br />
heckman selection model, [R] heckman,<br />
[R] heckoprobit<br />
interval regression, [R] intreg<br />
linear regression, [R] cnsreg<br />
seemingly unrelated, [R] sureg<br />
stochastic frontier, [R] frontier<br />
three-stage least squares, [R] reg3<br />
truncated, [R] truncreg<br />
logistic regression, [R] logistic, [R] logit, also see<br />
logit regression subentry<br />
conditional, [R] clogit<br />
multinomial, [R] mlogit<br />
ordered, [R] ologit<br />
skewed, [R] scobit<br />
stereotype, [R] slogit<br />
logit regression, [R] logit, also see logistic regression<br />
subentry<br />
for grouped data, [R] glogit<br />
nested, [R] nlogit<br />
maximum likelihood estimation, [R] ml<br />
multilevel mixed-effects, [ME] mecloglog,<br />
[ME] meglm, [ME] melogit, [ME] menbreg,<br />
[ME] meologit, [ME] meoprobit,<br />
[ME] mepoisson, [ME] meprobit<br />
multinomial<br />
logistic regression, [R] mlogit<br />
probit regression, [R] mprobit<br />
negative binomial regression, [R] nbreg<br />
truncated, [R] tnbreg<br />
zero-inflated, [R] zinb<br />
parametric survival models, [ST] streg<br />
Poisson regression, [R] poisson<br />
truncated, [R] tpoisson<br />
zero-inflated, [R] zip<br />
probit regression, [R] probit<br />
bivariate, [R] biprobit<br />
for grouped data, [R] glogit<br />
heteroskedastic, [R] hetprobit<br />
multinomial, [R] mprobit<br />
ordered, [R] oprobit<br />
with endogenous regressors, [R] ivprobit<br />
with sample selection, [R] heckprobit<br />
programming, [P] makecns