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RE: st: Confirming whether a variable is binary or continuous


From   Cameron McIntosh <cnm100@hotmail.com>
To   STATA LIST <statalist@hsphsun2.harvard.edu>
Subject   RE: st: Confirming whether a variable is binary or continuous
Date   Sun, 18 Mar 2012 23:02:42 -0400

I think that the only way to decide how to proceed is to first approach this issue conceptually (i.e, think about it) -- based on your content area expertise, is the covariate in question truly binary (qualitative) or do the observed categories merely discretize a latent continuous process? If the former, you can use observed categorical variable methodology to examine the covariate distributions by treatment group. (e.g., chi-square tests of independence and related methods for contingency tables); if the latter, then you may be into tetrachorics and the like. 
MacDonald, P.L., & Gardner, R.C. (2000). Type I Error Rate Comparisons of Post Hoc Procedures for I j Chi-Square Tables. Educational and Psychological Measurement, 60(5), 735-754.

Bentler, P.M. (2011). Can Interval-level Scores be Obtained from Binary Responses? UCLA Preprint #622.http://preprints.stat.ucla.edu/622/Bentler%20Interval%20Scores%20from%20Binary%20Responses.pdf

Ulrich, R., & Wirtz, M. (2004). On the correlation of a naturally and an artificially dichotomized variable. British Journal of Mathematical and Statistical Psychology, 57(2), 235–251. 

Ledesma, R.D., Macbeth, G., & Valero-Mora, P. (2011). Software for Computing the Tetrachoric Correlation Coefficient. Revista Latinoamericana de Psicología, 43(1), 181-189. http://openjournal.konradlorenz.edu.co/index.php/rlpsi/article/viewFile/459/463

Greer, T., Dunlap, W.P., & Beatty, G.O. (2003). A Monte Carlo Evaluation of the Tetrachoric Correlation Coefficient. Educational and Psychological Measurement, 63(6), 931-950.

Bonett, D.G., & Price, R.M. (2005). Inferential Methods for the Tetrachoric Correlation Coefficient. Journal of Educational and Behavioral Statistics, 30(2), 213-225.

Long, M.A., Berry, K.J., & Milke, P.W., Jr. (2009). Tetrachoric Correlation: A Permutation Alternative. Educational and Psychological Measurement, 69(3), 429-437.

Genest, C., & Lévesque, J.-M. (2009). Estimating correlation from dichotomized normal variables. Journal of Statistical Planning and Inference, 139(11), 3785-3794.

Choi, J., Peters, M., & Mueller, R.O. (2010). Correlational analysis of ordinal data: from Pearson’s r to Bayesian polychoric correlation. Asia Pacific Education Review, 11(4), 459-466. 

Cam

> Date: Mon, 19 Mar 2012 00:28:27 +0000
> Subject: Re: st: Confirming whether a variable is binary or continuous
> From: njcoxstata@gmail.com
> To: statalist@hsphsun2.harvard.edu
> 
> Your program just echoes its own input, confirming that what you
> specify is a binary variable is indeed binary and what you specify is
> a continuous variable is indeed continuous. It does no checking
> whatsoever.
> 
> I am puzzled about why you think that is useful and indeed in what
> sense it is a solution to your original problem.
> 
> Nick
> 
> On Sun, Mar 18, 2012 at 5:07 PM, Bert Jung <bjung59@gmail.com> wrote:
> 
> > Thanks all for these helpful insights.  I wanted to share my solution
> > which, if clumsy, works for me.  The basic idea is to check whether a
> > particular variable is part of the continuous or binary varlist and
> > then proceed as appropriate.
> >
> > This approach keeps intact the order specified in varlist.  I am
> > collecting estimation output and wanted the order to remain as
> > specified by the user.
> >
> > This is just a minimum working example, obviously various checks and
> > balances are of order.
> >
> > Cheers Bert
> >
> >
> >
> > cap program drop varcheck
> > program varcheck, nclass
> >
> >        syntax varlist, contvars(varlist) binaryvars(varlist)
> >
> >        * Loop over all variables in varlist; this approach keeps the order
> > in -varlist- intact
> >        foreach v of local varlist {
> >
> >                * (a) Is variable part of the variables specified in "contvars"?
> >                local contvar: list v in contvars
> >
> >                if `contvar'==1 {
> >                        di "`v' is specified as continuous variable"
> >                }
> >
> >
> >                * (b) Is variable part of the variables specified in "binaryvars"?
> >                local propvar: list v in binaryvars
> >
> >                if `propvar'==1 {
> >                        di "`v' specified as binary variable"
> >                }
> >        }
> >
> > end
> >
> >
> > sysuse auto, clear
> >
> > varcheck mpg price foreign weight, contvars(mpg price weight)
> > binaryvars(foreign)
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> >
> > On Sun, Mar 18, 2012 at 7:40 AM, Alexander Jais <jais@win.rwth-aachen.de> wrote:
> >> Sorry, stimmt ist bei mir noch als to do - kommt die Woche.
> >>
> >> Bist wieder aus INdien zurück - wie wars?
> >>
> >> LG
> >> Alex
> >>
> >> On 03/16/12, Bert Jung  <bjung59@gmail.com> wrote:
> >>
> >>> Dear Statalisters,
> >>>
> >>> I am writing a short program to make a balance table that compares
> >>> covariates across a treatment and control group.  I am looking for a
> >>> way to confirm whether a variable is binary in order to use -prtest-
> >>> for proportions rather than -ttest- for continous variables.
> >>>
> >>> One option is to check the actual data values and do -prtest- if there
> >>> are only 0's and 1's.  But a continuous but rare outcome could
> >>> accidentally also take these values, e.g. the number of
> >>> hospitalizations in the past 3 months.
> >>>
> >>> Is there a safer way to confirm that a variable is binary?
> >>>
> >>> Thanks for any pointers,
> >>> Bert
> 
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