[R-sig-ME] lme with interaction: how to decide which treatment is more efficaceous? how to deal with p value column of the lme summary?
Martina Giovannella
martina.giovannella at icfo.es
Mon Mar 21 16:58:49 CET 2016
I am using an lme to check the effect of 3 types of treatment (A,B, C)
on my variable, over time. I do not expect any effect of treatment A,
which is a fake treatment.
I have measurement over 5 periods,on 2 sides.
My question is: for each treatment and each period, is my variable
different from the reference point (treatment A, period 1)?
My model is
lme(var ~ treatment*period+side,
method="ML",
random=list(IDlog=~1), na.action=na.omit,
data=changes)
This is the anova of the model
numDF denDF F-value p-value
(Intercept) 1 473 79.36094 <.0001
treatment 2 473 3.49473 0.0311
period 4 473 12.51296 <.0001
side 1 473 12.16210 0.0005
treatment:period 8 473 2.02865 0.0416
and the summary for fixed effects
Fixed effects: var ~ treatment * period + hemisphere
Value Std.Error DF t-value p-value
(Intercept) 4.622038 3.180983 473 1.453022 0.1469
treatmentB -1.376755 3.703398 473 -0.371754 0.7102
treatmentC -1.113021 3.703398 473 -0.300540 0.7639
period2 3.799946 4.168792 473 0.911522 0.3625
period3 6.124463 4.168792 473 1.469122 0.1425
period4 4.309267 4.168792 473 1.033697 0.3018
period5 5.482068 4.168792 473 1.315026 0.1891
sideright -4.278672 1.226887 473 -3.487420 0.0005
treatmentB:period2 4.059350 5.190104 473 0.782133 0.4345
treatmentC:period2 7.508426 5.190104 473 1.446681 0.1486
treatmentB:period3 1.965207 5.190104 473 0.378645 0.7051
treatmentC:period3 5.312525 5.190104 473 1.023587 0.3066
treatmentB:period4 9.031016 5.190104 473 1.740045 0.0825
treatmentC:period4 7.819397 5.190104 473 1.506597 0.1326
treatmentB:period5 13.620365 5.190104 473 2.624295 0.0090
treatmentC:period5 4.224340 5.215896 473 0.809897 0.4184
The anova states the treatment has an effect, period as well, and there
is an interaction between treatment and period. Sides are different.
This is what I expected.
How can I use the p values columns to state for which treatment and
which period I see a difference from the reference value?
What I would like to retrieve is the numbers I obtain when I test each
treatment separately. I know how to obtain the mean, what I have to sum
up in the value column. What about the p values?
Treatment A
Fixed effects: var ~ period + hemisphere
Value Std.Error DF t-value p-value
(Intercept) 1.849555 3.768596 94 0.4907810 0.6247
period2 3.799946 4.174739 94 0.9102236 0.3650
period3 6.124463 4.174739 94 1.4670291 0.1457
period4 4.309267 4.174739 94 1.0322244 0.3046
period5 5.482068 4.174739 94 1.3131524 0.1923
sideright -1.142925 2.640337 94 -0.4328710 0.6661
Anova
numDF denDF F-value p-value
(Intercept) 1 94 4.967367 0.0282
period 4 94 0.654946 0.6248
side 1 94 0.187377 0.6661
Treatment B
Fixed effects: var ~ period + hemisphere
Value Std.Error DF t-value p-value
(Intercept) 4.674863 2.938724 175 1.590780 0.1135
period2 7.859296 3.241315 175 2.424724 0.0163
period3 8.089670 3.241315 175 2.495799 0.0135
period4 13.340283 3.241315 175 4.115700 0.0001
period5 19.102433 3.241315 175 5.893420 0.0000
sideright -7.137831 2.049988 175 -3.481889 0.0006
Anova
numDF denDF F-value p-value
(Intercept) 1 175 34.37766 <.0001
period 4 175 9.60042 <.0001
side 1 175 12.12355 6e-04
Treatment C
Fixed effects: var ~ period + hemisphere
Value Std.Error DF t-value p-value
(Intercept) 2.936039 2.166417 173 1.355251 0.1771
period2 11.308372 2.392119 173 4.727346 0.0000
period3 11.436988 2.392119 173 4.781112 0.0000
period4 12.128664 2.392119 173 5.070260 0.0000
period5 9.949632 2.428331 173 4.097314 0.0001
sideright -3.132715 1.520530 173 -2.060278 0.0409
Anova
numDF denDF F-value p-value
(Intercept) 1 173 58.13208 <.0001
period 4 173 8.99083 <.0001
side 1 173 4.24474 0.0409
From this test it is very clear that for treatment A, var is not bigger
in any period respect to the reference point, while it is for treatment
B and C; right side smaller than left.
I want to obtain this information using the first model, with the 3
treatments.
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