RE: Missing Gender (Categorical values)

From: Diane Mould Date: July 30, 2002 technical Source: cognigencorp.com
From:"diane r mould" Subject:RE: [NMusers] Missing Gender (Categorical values) Date: Tue, 30 Jul 2002 16:49:05 -0400 Dear All I would think that you should be able to get some good information for imputation from other covariate data such as weight, creatinine clearance, age etc. So even if a sex effect on the PK or PD of a drug is not well established, one should be able to create a covariate based model that is not unreasonable for use with multiple imputation. Then you could use the covariate information (including the sex data) as your DV and use the Likelihood option as Nick suggested. Diane
Jul 30, 2002 Atul Bhattaram Venkatesh Missing Gender (Categorical values)
Jul 30, 2002 Nick Holford Re: Missing Gender (Categorical values)
Jul 30, 2002 Nick Holford Not enough sex!
Jul 30, 2002 Alan Xiao Re: Missing Gender (Categorical values)
Jul 30, 2002 Diane Mould RE: Missing Gender (Categorical values)
Jul 30, 2002 Leonid Gibiansky Re: Not enough sex!
Jul 30, 2002 Nick Holford Re: Missing Gender (Categorical values)
Jul 30, 2002 Stephen Duffull RE: Missing Gender (Categorical values)
Jul 31, 2002 William Bachman RE: Missing Gender (Categorical values) - my $0.02
Jul 31, 2002 Lewis B. Sheiner Re: Missing Gender (Categorical values) - my $0.02
Jul 31, 2002 Alan Xiao Re: Missing Gender (Categorical values)
Jul 31, 2002 Serge Guzy RE: Missing Gender (Categorical values)
Jul 31, 2002 Alan Xiao Re: Missing Gender (Categorical values)
Jul 31, 2002 Nick Holford Re: Missing Gender (Categorical values)
Jul 31, 2002 Diane Mould RE: Missing Gender (Categorical values)
Aug 05, 2002 Alan Xiao Re: Missing Gender (Categorical values)
Aug 06, 2002 Diane Mould RE: Missing Gender (Categorical values)