Dorothee wrote:
Hello,
I am running polychoric correlations on a dataset composed of 12 ordinal and
binary variables (N =384), using the polycor package.
One of the association (between 2 dichotomous variables) is very high using
the 2-step estimate (0.933 when polychoric run only between the two
variables; but 0.801 when polychoric run on the 12 variables). The same
correlation run with ML estimate returns a singularity message.
First, I would like to know why the estimations between only the two
dichotomous variables and with all the variables at once (with the 2-step
estimate) returns slightly different results.
Secondly, when i checked back the distribution of these two dichotomous
variables they appear about symmetrically opposed. Therefore, one should
indeed expect a strong association between them, but a negative one, isn't
it? Why does the polychoric correlation returns a positive coefficient? What
does it mean for the rest of the coefficients, should i trust them?
I have to say I'm new to R and not very strong in statistics, I hope I
haven't posted a stupid question...
Hi Dorothee,
This may be similar to a problem I encountered with the biserial.cor
function, where the default specification of which value of the
dichotomous variable to use as the reference value gave me a correlation
coefficient with an apparently reversed sign. It might be that your the
values of your categorial variable are not in the order you assume.
Jim
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