On 21 Apr 2002 09:04:03 -0700, [EMAIL PROTECTED] (wuzzy) wrote: ... > Maybe when using the variable as a covariate it is good to > dichotomize? > > Say you wanted to adjust for energy (in METs) expended during > work-related activity. Is it better to adjust for the continuous > variable, energy, or is it better to adjust for quartiles of energy. > (ie. Q1=office-type Q4=fireman)
How bad is your variable scored? Does it need to be transformed for it to have linear effects on outcome? If you have enough degrees of freedom, you *can* do things with covariates, for *control* purposes, that you would not do with something you are testing. For instance, you can control by "narrow age group" by having a factor with each age, by year. That is exactly equivalent to having dummy variables for covariates, for each year. But the linear of effect for age is usually 90% or more of what is there, and it is both easier to look at analyses, and to explain them, if you don't have 40 extra covariates. Having a second variable for Age might do most of the rest -- either providing a quadratic fit, or a spline (essentially, use two regression lines). > > the quartiles(dichotomized) might cause a loss of information but it > might "adjust" for the variable better by filtering out groups of > people? am I wrong? IF there are real groups, your best control is to have covariates that match/ describe the real groups (with large enough N that you are screwing up your analysis by capitalizing on chance). "Effect coding" is what it has been called, when you put in a covariate that *uses* the observed mean as its score: This implies that a correction will be needed to adjust the residual d.f., according to how many 'means' have been employed. - I don't know that anyone does this in analyses these days, since I ran into the technique in an old book that was advising how to perform repeated measures ANOVA with a little missing data, especially when using small-capacity computers. Hope this helps. -- Rich Ulrich, [EMAIL PROTECTED] http://www.pitt.edu/~wpilib/index.html . . ================================================================= Instructions for joining and leaving this list, remarks about the problem of INAPPROPRIATE MESSAGES, and archives are available at: . http://jse.stat.ncsu.edu/ . =================================================================
