Stata 15 help for cc

[R] epitab -- Tables for epidemiologists (cc and cci)

Syntax

cc var_case var_exposed [if] [in] [weight] [, cc_options]

cci #a #b #c #d [, cci_options]

cc_options Description ------------------------------------------------------------------------- Options by(varname [, missing]) stratify on varname estandard combine external weights with within-stratum statistics istandard combine internal weights with within-stratum statistics standard(varname) combine user-specified weights with within-stratum statistics pool display pooled estimate nocrude do not display crude estimate nohom do not display homogeneity test bd perform Breslow-Day homogeneity test tarone perform Tarone's homogeneity test binomial(varname) number of subjects variable cornfield use Cornfield approximation to calculate CI of the odds ratio woolf use Woolf approximation to calculate SE and CI of the odds ratio exact calculate Fisher's exact p level(#) set confidence level; default is level(95) -------------------------------------------------------------------------

cci_options Description ------------------------------------------------------------------------- cornfield use Cornfield approximation to calculate CI of the odds ratio woolf use Woolf approximation to calculate SE and CI of the odds ratio exact calculate Fisher's exact p level(#) set confidence level; default is level(95) ------------------------------------------------------------------------- fweights are allowed; see weight.

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cc

Statistics > Epidemiology and related > Tables for epidemiologists > Case-control odds ratio

cci

Statistics > Epidemiology and related > Tables for epidemiologists > Case-control odds-ratio calculator

Description

cc is used with case-control and cross-sectional data. It calculates point estimates and confidence intervals for the odds ratio, along with attributable or prevented fractions for the exposed and total population. cci is the immediate form of cc; see immed. Also see [R] logistic for related commands.

Options for cc

+---------+ ----+ Options +----------------------------------------------------------

by(varname [, missing]) specifies that the tables be stratified on varname. Missing categories in varname are omitted from the stratified analysis, unless option missing is specified within by(). Within-stratum statistics are shown and then combined with Mantel-Haenszel weights. If estandard, istandard, or standard() is also specified (see below), the weights specified are used in place of Mantel-Haenszel weights.

estandard, istandard, and standard(varname) request that within-stratum statistics be combined with external, internal, or user-specified weights to produce a standardized estimate. These options are mutually exclusive and can be used only when by() is also specified. (When by() is specified without one of these options, Mantel-Haenszel weights are used.)

estandard external weights are the number of unexposed controls.

istandard internal weights are the number of exposed controls. istandard can be used to produce, among other things, standardized mortality ratios (SMRs).

standard(varname) allows user-specified weights. varname must contain a constant within stratum and be nonnegative. The scale of varname is irrelevant.

pool specifies that, in a stratified analysis, the directly pooled estimate also be displayed. The pooled estimate is a weighted average of the stratum-specific estimates using inverse-variance weights, which are the inverse of the variance of the stratum-specific estimate. pool is relevant only if by() is also specified.

nocrude specifies that in a stratified analysis the crude estimate -- an estimate obtained without regard to strata -- not be displayed. nocrude is relevant only if by() is also specified.

nohom specifies that a chi-squared test of homogeneity not be included in the output of a stratified analysis. This tests whether the exposure effect is the same across strata and can be performed for any pooled estimate -- directly pooled or Mantel-Haenszel. nohom is relevant only if by() is also specified.

bd specifies that Breslow and Day's chi-squared test of homogeneity be included in the output of a stratified analysis. This tests whether the exposure effect is the same across strata. bd is relevant only if by() is also specified.

tarone specifies that Tarone's chi-squared test of homogeneity, which is a correction to the Breslow-Day test, be included in the output of a stratified analysis. This tests whether the exposure effect is the same across strata. tarone is relevant only if by() is also specified.

binomial(varname) supplies the number of subjects (cases plus controls) for binomial frequency records. For individual and simple frequency records, this option is not used.

cornfield requests that the Cornfield (1956) approximation be used to calculate the confidence interval of the odds ratio. By default, cc reports an exact interval.

woolf requests that the Woolf (1955) approximation, also known as the Taylor expansion, be used for calculating the standard error and confidence interval for the odds ratio. By default, cc reports an exact interval.

exact requests that Fisher's exact p be calculated rather than the chi-squared and its significance level. We recommend specifying exact whenever samples are small. When the least-frequent cell contains 1,000 cases or more, there will be no appreciable difference between the exact significance level and the significance level based on the chi-squared, but the exact significance level will take considerably longer to calculate. exact does not affect whether exact confidence intervals are calculated. Commands always calculate exact confidence intervals where they can, unless cornfield or woolf is specified.

level(#) specifies the confidence level, as a percentage, for confidence intervals. The default is level(95) or as set by set level.

Options for cci

cornfield requests that the Cornfield (1956) approximation be used to calculate the confidence interval of the odds ratio. By default, cci reports an exact interval.

woolf requests that the Woolf (1955) approximation, also known as the Taylor expansion, be used for calculating the standard error and confidence interval for the odds ratio. By default, cci reports an exact interval.

exact requests that Fisher's exact p be calculated rather than the chi-squared and its significance level. We recommend specifying exact whenever samples are small. When the least-frequent cell contains 1,000 cases or more, there will be no appreciable difference between the exact significance level and the significance level based on the chi-squared, but the exact significance level will take considerably longer to calculate. exact does not affect whether exact confidence intervals are calculated. Commands always calculate exact confidence intervals where they can, unless cornfield or woolf is specified.

level(#) specifies the confidence level, as a percentage, for confidence intervals. The default is level(95) or as set by set level.

Examples

--------------------------------------------------------------------------- Setup . webuse ccxmpl

List the data . list

Calculate odds ratio, etc. . cc case exposed [fw=pop]

Immediate form of above command . cci 4 386 4 1250

Same as above, but calculate Fisher's exact p rather than the chi-squared . cci 4 386 4 1250, exact

--------------------------------------------------------------------------- Setup . webuse downs

List the data . list

Perform stratified analysis of the odds ratio . cc case exposed [fw=pop], by(age)

Same as above, but report Tarone's chi-squared test of homogeneity . cc case exposed [fw=pop], by(age) tarone ---------------------------------------------------------------------------

Video examples

Odds ratios for case-control data

Stratified analysis of case-control data

Odds ratios calculator

Stored results

cc and cci store the following in r():

Scalars r(p) two-sided p-value r(p1_exact) one-sided p-value for Fisher's exact test r(p_exact) two-sided p-value for Fisher's exact test r(or) odds ratio r(lb_or) lower bound of CI for or r(ub_or) upper bound of CI for or r(afe) attributable (prev.) fraction among exposed r(lb_afe) lower bound of CI for afe r(ub_afe) upper bound of CI for afe r(afp) attributable fraction for the population r(crude) crude estimate (cc only) r(lb_crude) lower bound of CI for crude r(ub_crude) upper bound of CI for crude r(pooled) pooled estimate (cc only) r(lb_pooled) lower bound of CI for pooled r(ub_pooled) upper bound of CI for pooled r(chi2_p) pooled heterogeneity chi-squared r(chi2_bd) Breslow-Day chi-squared r(df_bd) degrees of freedom for Breslow-Day chi-squared r(chi2_t) Tarone chi-squared r(df_t) degrees of freedom for Tarone chi-squared r(df) degrees of freedom r(chi2) chi-squared

References

Cornfield, J. 1956. A statistical problem arising from retrospective studies. In Vol. 4 of Proceedings of the Third Berkeley Symposium, ed. J. Neyman, 135-148. Berkeley, CA: University of California Press.

Woolf, B. 1955. On estimating the relation between blood group disease. Annals of Human Genetics 19: 251-253. Reprinted in Evolution of Epidemiologic Ideas: Annotated Readings on Concepts and Methods, ed. S. Greenland, pp. 108-110. Newton Lower Falls, MA: Epidemiology Resources.


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