-mrunning- and -mlowess- are possible graphical aids here, giving
smooths of response versus each predictor, with adjustment for other
predictors. Use -findit- to identify locations of program files.
Nick
[email protected]
Austin Nichols
Andrea--
I strongly disagree with Martin Weiss, SamL, and Branko milanovic who
claim that an ordered categorical explanatory variable can be included
as a sensible regressor without justification. Creating dummies *is*
justifiable; you are merely computing conditional means. Including
income (or "trust") as a single explanatory variable when income (or
"trust") is measured as an ordered categorical explanatory variable
requires a strong assumption that the effect is linear in the index of
categories. The dummy variable approach requires no such assumption.
As Richard Williams quite rightly points out, you can -test- whether
the effect is linear in the index, or whether groups of individual
dummies all have the same effect. One useful way is to create dummies
that correspond to more interpretable groups, like above the median,
more than twice the median, less than half the median, etc. so you can
see directly from the regression output where deviations from
linearity occur... graphs are also helpful for this purpose.
*
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