Dear all,
I have a lme model with in.studm = time since beginning of observation,
and sc10m = psychological impairment.
I want to know the interaction of phase1f (factor 0,1) and anf.kosm
(continuous), but not the main effects of theses variables.
When I run
a.lme <- lme(data = alle.pt, random = ~in.studm | code, fixed = sc10m ~
phase1f * anf.kosm, na.action = na.omit)
I get
Fixed effects: sc10m ~ phase1f * anf.kosm
Value Std.Error DF t-value p-value
(Intercept) 0.8930910 0.03638889 1966 24.54296 <.0001
phase1f -0.1263110 0.01838107 1966 -6.87180 <.0001
anf.kosm 0.0066864 0.00672424 604 0.99437 0.3204
phase1f:anf.kosm 0.0043765 0.00336473 1966 1.30069 0.1935
but when I run
b.lme <- lme(data = alle.pt, random = ~in.studm | code, fixed = sc10m ~
phase1f : anf.kosm, na.action = na.omit)
I get
Fixed effects: sc10m ~ phase1f:anf.kosm
Value Std.Error DF t-value p-value
(Intercept) 0.8333118 0.03527006 1966 23.62660 <.0001
phase1f0anf.kosm 0.0279751 0.00703025 1966 3.97925 0.0001
phase1f1anf.kosm -0.0009885 0.00684771 1966 -0.14435 0.8852
i.e. two coefficients for phase1f : anf.kosm, but phase1f (defined as
factor) has only two levels (0 and 1). This also happens when I remove
the main effects from a.lme via the "update" function. It does not
happen for an interaction among two continuous variables.
I do not understand why this occurs/where the mistake is. I would be
grateful for any comments/ideas.
Best wishes
Bernd
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