[R] When models and anova(model) disagree...

[Rob James]

I have a situation where the parameter estimates from lrm identify a 
binary predictor variable ("X") as clearly non-significant (p>0.3), but 
the ANOVA of that same model gives X  a chi^2-df rank of > 200, and 
adjudicates X  and one interaction of X and a continuous measure as 
highly significant.  The N is massive and X has two categories, each 
with > 100,000 observations.  I would expect X to have a significant 
impact on the outcome.

The full model includes a large number of continuous (coded with rcs 
with 3 knots)  and categorical variables, as well as a plethora of 
interactions between the categorical and continuous variables. Only one 
of the interactions between the binary variable and the other 
categorical or continuous variables is statistically significant.

Can anyone offer a suggestion on what might explain this discordance?