I want to ask some confusing in my mind regarding the data analysis:
I have conducting the experimental trial in repeated measure by hours as below:
Design: Completely Randomized Design--(in green houses)-there are 6 box unit
========================================================
- 1 Treatment (2 levels): level A and B
- Replicate: 3 replication
- Response was recorded by hours (repeated measure) from 24 hours (poisson distribution)
This follows as linear mixed model.
and I used $R$ to process my data by using this syntax:
OUTPUT is:
>
**MY QUESTION IS: is my syntax above TRUE?**
Thanks in advanced
I have conducting the experimental trial in repeated measure by hours as below:
Design: Completely Randomized Design--(in green houses)-there are 6 box unit
========================================================
- 1 Treatment (2 levels): level A and B
- Replicate: 3 replication
- Response was recorded by hours (repeated measure) from 24 hours (poisson distribution)
This follows as linear mixed model.
and I used $R$ to process my data by using this syntax:
Code:
>Random intercepts for 3 rep but time and treat effects are fixed
>model1 <-lmer(respon~ treat * time + rep + (1|rep), data=data, family = poisson)
>
Code:
model1
Generalized linear mixed model fit by the Laplace approximation
Formula: respon ~ treat * time + rep + (1 | rep)
Data: data
AIC BIC logLik deviance
720 740 -354 708
Random effects:
Groups Name Variance Std.Dev.
rep (Intercept) 0.0078266 0.088468
Number of obs: 207, groups: rep, 3
Fixed effects
Estimate Std. Error z value Pr(>|z|)
(Intercept) 0.843199 0.311791 2.7044 0.00684 **
treat -0.246484 0.124762 -1.9756 0.04820 *
time 0.010138 0.016759 0.6049 0.54523
rep 0.063730 0.082557 0.7719 0.44015
treat:time 0.009520 0.008028 1.1858 0.23569
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
**MY QUESTION IS: is my syntax above TRUE?**
Thanks in advanced