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From |
"DEBORAH L. HUANG" <huangdx@u.washington.edu> |

To |
statalist@hsphsun2.harvard.edu |

Subject |
Re: st: Code to generate dummy variable from several categorical variables? |

Date |
Tue, 17 Jan 2012 11:39:53 -0800 (PST) |

Basically what I'm hoping to do is "collapse" the outcome variables A, B and C (all binary) into the new outcome indicator variable abnlX for ANOVA (e.g., comparison mean age across indicators, among other continuous demographic variables). The new outcome variable abnlX would have 3 indicators (my mistake in the earlier message). As an indicator variable abnlX would be defined as follows: abnlX indicator #1 =0 if A is 0 or missing, B is 0/1/missing, C is 0/1/missing; =1 if A is 1, B is 0/1/missing, C is 0/1/missing abnlX indicator #2 =0 if B is 0 or missing, A is 0/1/missing, C is 0/1/missing; =1 if B is 1, A is 0/1/missing, C is 0/1/missing abnlX indicator #3 =0 if C is 0 or missing, A is 0/1/missing, B is 0/1/missing; =1 if C is 1, A is 0/1/missing, C is 0/1/missing Alternately for a categorical outcome variable abnlX it would be defined as follows: abnlX=0 if A=0 or missing & B=0 or missing & C=0 or missing abnlX=1 if A=1 & B=0/1/missing & C=0/1/missing abnlX=2 if B=1 & A=0/1/missing & C=0/1/missing abnlX=3 if C=1 & A=0/1/missing & B=0/1/missing Thank you again to everyone for your input, and hopefully this further clarifies my question. Deborah Huang On Tue, Jan 17, 2012 at 7:22 AM, David Hoaglin <dchoaglin@gmail.com> wrote:

It would help to have further clarification. As Nick pointed out, an indicator variable (aka dummy variable) has two (non-missing) >values: 0 and 1. Please explain what you mean by "a dummy variable with 4 indicators" and >then give an explicit definition of the desired "dummy variable" in terms of A, B, and C. If you actually want a categorical variable with 4 categories (which would necessarily be >mutually exclusive), please define those categories in terms of A, B, and C. Your explanation of the "dummy variable" abnlX lists three indicator variables. If you >intend abnlX to be a categorical variable, those three indicators are not mutually exclusive. It would help if you described the role that the new variable will play in an analysis. >Some regression models, for example, could include the binary variables A, B, and C as they >stand; they would not need to be mutually exclusive. BTW, three binary variables yield 8 possible combinations. The one not in your list is A=1, >B=0, C=1. Why is it necessary to re-categorize this subject and subjects #2, #3, and #5? David Hoaglin

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**Follow-Ups**:**Re: st: Code to generate dummy variable from several categorical variables?***From:*David Hoaglin <dchoaglin@gmail.com>

**RE: st: Code to generate dummy variable from several categorical variables?***From:*Nick Cox <n.j.cox@durham.ac.uk>

**st: NetCourse 631 survival analysis***From:*Lars Folkestad <lfolkestad@health.sdu.dk>

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