Dear colleagues,
I am analyzing a data set of 68 values (integers). In some treatments (exactly
6) the values are "zero". Because I record 0 in my measurement (or really a
small value below zero)
My experiment is designed in such a way that I record values for 6 treatments
at 2 times. Replicates are different in each combination time-treatment.
I am running a GLM , poisson distribution, for ANOVA I used Chisq, and for the
POST HOC test I used Tukey.
I try to detect if interaction is significant, so I build the script:
expresion~time*treatment
Effects of time, treatment are interaction are significant. However, when I run
the script for Tukey comparisons, I only get 15 comparisons. Of course I cannot
interpret that:
these comparisons are the same for Time 1 and Time 2, since there is a
significant effect of time. Moreover, I got a warning message : covariate
interactions found. I dont know if I am doing right? I dont know what to do?
Thank you for your help,
Xavier
PhD Student
University of Neuchatel
lm3=glm(expresion~time*treatment,family="poisson")
> summary(lm3)
Call:
glm(formula = expresion ~ time * treatment, family = "poisson")
Deviance Residuals:
Min 1Q Median 3Q Max
-5.3796 -1.4523 -0.6642 1.2277 6.3909
Coefficients:
Estimate Std. Error z value Pr(>|z|)
(Intercept) 2.09964 0.29508 7.115 1.12e-12 ***
time 0.20294 0.19255 1.054 0.291895
treatmentCHA0+Db -0.17004 0.36180 -0.470 0.638356
treatmentDb 1.68952 0.37624 4.490 7.11e-06 ***
treatmentHEALTHY 0.84035 0.50340 1.669 0.095049 .
treatmentPCL 0.32072 0.37950 0.845 0.398041
treatmentPCL+Db 0.54365 0.34047 1.597 0.110320
time:treatmentCHA0+Db 0.87314 0.22626 3.859 0.000114 ***
time:treatmentDb -0.82803 0.26539 -3.120 0.001808 **
time:treatmentHEALTHY -1.36987 0.38318 -3.575 0.000350 ***
time:treatmentPCL 0.08474 0.24635 0.344 0.730851
time:treatmentPCL+Db 0.39244 0.21521 1.824 0.068217 .
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Dispersion parameter for poisson family taken to be 1)
Null deviance: 1173.05 on 66 degrees of freedom
Residual deviance: 403.07 on 55 degrees of freedom
AIC: 707.95
Number of Fisher Scoring iterations: 5
> anova(lm3,test="Chisq")
Analysis of Deviance Table
Model: poisson, link: log
Response: expresion
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev Pr(>Chi)
NULL 66 1173.05
time 1 100.55 65 1072.50 < 2.2e-16 ***
treatment 5 561.69 60 510.81 < 2.2e-16 ***
time:treatment 5 107.75 55 403.07 < 2.2e-16 ***
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
> summary(glht(lm3, mcp(treatment="Tukey")))
Simultaneous Tests for General Linear Hypotheses
Multiple Comparisons of Means: Tukey Contrasts
Fit: glm(formula = expresion ~ time * treatment, family = "poisson")
Linear Hypotheses:
Estimate Std. Error z value Pr(>|z|)
CHA0+Db - CHA0 == 0 -0.1700 0.3618 -0.470 0.9970
Db - CHA0 == 0 1.6895 0.3762 4.490 <0.001 ***
HEALTHY - CHA0 == 0 0.8404 0.5034 1.669 0.5402
PCL - CHA0 == 0 0.3207 0.3795 0.845 0.9568
PCL+Db - CHA0 == 0 0.5437 0.3405 1.597 0.5892
Db - CHA0+Db == 0 1.8596 0.3135 5.931 <0.001 ***
HEALTHY - CHA0+Db == 0 1.0104 0.4584 2.204 0.2266
PCL - CHA0+Db == 0 0.4908 0.3174 1.546 0.6231
PCL+Db - CHA0+Db == 0 0.7137 0.2696 2.648 0.0817 .
HEALTHY - Db == 0 -0.8492 0.4699 -1.807 0.4491
PCL - Db == 0 -1.3688 0.3338 -4.101 <0.001 ***
PCL+Db - Db == 0 -1.1459 0.2887 -3.969 <0.001 ***
PCL - HEALTHY == 0 -0.5196 0.4725 -1.100 0.8764
PCL+Db - HEALTHY == 0 -0.2967 0.4418 -0.672 0.9842
PCL+Db - PCL == 0 0.2229 0.2929 0.761 0.9725
---
Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
(Adjusted p values reported -- single-step method)
Warning message:
In mcp2matrix(model, linfct = linfct) :
covariate interactions found -- default contrast might be inappropriate
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