Because they test different hypothesis.
ir. Thierry Onkelinx
Instituut voor natuur- en bosonderzoek / Research Institute for Nature and
Forest
team Biometrie & Kwaliteitszorg / team Biometrics & Quality Assurance
Kliniekstraat 25
1070 Anderlecht
Belgium
To call in the statistician after the experiment is done may be no more
than asking him to perform a post-mortem examination: he may be able to say
what the experiment died of. ~ Sir Ronald Aylmer Fisher
The plural of anecdote is not data. ~ Roger Brinner
The combination of some data and an aching desire for an answer does not
ensure that a reasonable answer can be extracted from a given body of data.
~ John Tukey
2015-05-26 21:46 GMT+02:00 li li <hannah.hlx at gmail.com>:
Thanks so much for replying.
Yes LimerTest package could be used to get pvalues when using lmer
function. But still the summary and anova function give different
pvalues.
Hanna
2015-05-26 15:19 GMT-04:00, byron vinueza <byronvinu_8 at hotmail.com>:
You can use the lmerTest package .
Enviado desde mi iPhone
El 26/5/2015, a las 13:18, li li <hannah.hlx at gmail.com> escribi?:
Hi all,
I am using the lme function to run a random coefficient model. Please
see
output (mod1) as below.
I need to obtain the pvalue for the fixed effect. As you can see,
the pvalues given using the summary function is different from the
resutls given in anova function.
Why should they be different and which one is the correct one to use?
Thanks!
Hanna
Linear mixed-effects model fit by REML
Data: minus20C1
AIC BIC logLik
-82.60042 -70.15763 49.30021
Random effects:
Formula: ~1 + months | lot
Structure: General positive-definite, Log-Cholesky parametrization
StdDev Corr
(Intercept) 8.907584e-03 (Intr)
months 6.039781e-05 -0.096
Residual 4.471243e-02
Fixed effects: ti ~ type * months
Value Std.Error DF t-value p-value
(Intercept) 0.25831245 0.016891587 31 15.292373 0.0000
type 0.13502089 0.026676101 4 5.061493 0.0072
months 0.00804790 0.001218941 31 6.602368 0.0000
type:months -0.00693679 0.002981859 31 -2.326329 0.0267
Correlation:
(Intr) typ months
type -0.633
months -0.785 0.497
type:months 0.321 -0.762 -0.409
Standardized Within-Group Residuals:
Min Q1 Med Q3 Max
-2.162856e+00 -1.962972e-01 -2.771184e-05 3.749035e-01 2.088392e+00
Number of Observations: 39
Number of Groups: 6
numDF denDF F-value p-value
(Intercept) 1 31 2084.0265 <.0001
type 1 4 10.8957 0.0299
months 1 31 38.3462 <.0001
type:months 1 31 5.4118 0.0267