[R] GLM and POST HOC test INTERPRETATION
Bert Gunter
bgunter.4567 at gmail.com
Thu Feb 9 01:45:26 CET 2017
Your questions are basically statistical and therefore OT here,
although some kind soul may respond. I would strongly suggest that you
consult with a local statistical expert, as you seem to be out of your
depth statistically.
Cheers,
Bert
Bert Gunter
"The trouble with having an open mind is that people keep coming along
and sticking things into it."
-- Opus (aka Berkeley Breathed in his "Bloom County" comic strip )
On Wed, Feb 8, 2017 at 4:08 PM, CHIRIBOGA Xavier
<xavier.chiriboga at unine.ch> wrote:
> 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
>
>
> [[alternative HTML version deleted]]
>
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