.- help for ^ccweight^ .-Create a weighting variable for analysing a case-control study --------------------------------------------------------------

^ccweight^ varlist [^,s^tatus^(^varname^)^ ^p^weight^(^varname^)^ ^c^pc^(^exp^)^ ]

Description -----------

^ccweight^ takes, as input, a varlist whose distinct values correspond to case groups, and a status variable (1 for cases, 0 for controls) in the option ^status^. It creates, as output, a new variable, suitable for use as a ^pweight^ variable when the case-control study is analysed by regression with robust variances.

Options for use with ^powercv^ ----------------------------

^status(^varname^)^ gives the name of a variable identifying cases. Nonzero nonmissing values are interpreted as cases, zero values as controls, and missing values as units of indeterminate status.

^pweight(^varname^)^ gives the name of a variable to contain the output weights. It is replaced if it exists, and generated otherwise. It is set to zero for orphan cases and controls and units of indeterminate status, to one for non-orphan cases, and, for non-orphan controls, to the case/control ratio amongst units in the same case group, multiplied by ^cpc^ (see below). If absent, this option defaults to the name ^_pweight^.

^cpc(^cpc^)^ is a scalar, real or integer expression, giving the number of controls per case to which the weights are adjusted. If absent, it defaults to one. This option does not affect the odds ratios or mean differences created by the regression, but may improve the aesthetics if the ^pweight^ is tabulated.

Remarks -------

This program is intended for use with ^logistic^ or other regression programs in case-control studies. The estimates are calculated as if there was a constant number of controls per case (given by ^cpc^) in all strata of the matching criterion defined by the varlist. Odds ratios (or other regression coefficients) are therefore calculated as for a hypothetical population, in which the matching criterion is distributed as for the (non-orphan) cases. The method is an alternative to conditional logistic regression for analysing unmatched studies, or matched studies with varying numbers of controls per case.

Examples --------

. ^ccweight age sex,st(case) pweight(pw)^

. ^ccweight casegp,st(status) cpc(4)^

Author ------

Roger Newson, Imperial College School of Medicine, London, UK. Email: ^r.newson@@ic.ac.uk^

Also see --------

Manual: ^[R] logistic^, ^[R] clogit^.