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<pre tabindex="0" class="GD40030CLR" style="font-family: Monospace; font-size: 10pt ! important; outline-style: none; border-style: none; white-space: pre-wrap ! important; margin: 0px; line-height: 1.3;"><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;"> Bom dia pessoal,
Bom já sei que esse assunto já foi motivo de tópicos passados no nosso mail-list e no internacional
,tem material na internet etc, mais essa saída do pacote contraste não entrou na minha cabeça
ainda não e venho pedir ajuda do grupo. Estou comparando minha variável resposta número de óvulos de
fêmeas de um parasitóide com as variáveis explicativa tratamento (com 2 níveis: 1 casal e 10 casais)
e geração (com 4 níveis: 3, 6, 9 e 12 gerações). Na saída da funcao contrast(), ele solta o trata-
mento </span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">10 casais no intercepto(imagino) e não faz as comparacoes dentro de cada geração, ele só desdobra
para o tratamento 1casal, mesmo assim sumiu com a geracao 12, onde pergunto onde que estou errando é
na funcao ou na interpretação? Sendo os argumentos que usei:
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">
> </span><span class="GD40030CCR ace_keyword" style="color: blue;">##Contraste tratamentos x desenvolvimento oviposicao a mumia
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">m.comple<-glm(des.ov.mu~tratamento*geracao,data=dados6, family="quasipoisson")
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">anova.comple<-anova(m.comple,test="Chi")
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">anova.comple
</span>Analysis of Deviance Table
Model: quasipoisson, link: log
Response: des.ov.mu
Terms added sequentially (first to last)
Df Deviance Resid. Df Resid. Dev P(>|Chi|)
NULL 82 9.1366
tratamento 1 1.0969 81 8.0397 2.265e-07 ***
geracao 3 2.2880 78 5.7518 4.445e-12 ***
tratamento:geracao 3 2.7715 75 2.9802 1.328e-14 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
<span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">#summary(m.comple)</span><span class="Apple-style-span" style="border-collapse: separate; color: rgb(0, 0, 0); font-family: Arial; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; font-size: medium;"><span class="Apple-style-span" style="font-family: Monospace; font-size: 13px; line-height: 17px; white-space: pre-wrap;"><pre tabindex="0" class="GD40030CLR" style="font-family: Monospace; font-size: 10pt ! important; outline-style: none; border-style: none; white-space: pre-wrap ! important; margin: 0px; line-height: 1.3;"><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">10 casais</span></pre></span></span>
<span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">#
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">##Fazendo os contrastes
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">require(contrast)
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">contr<-contrast(m.comple, list(geracao=levels(geracao),tratamento="1casal"),list(geracao=levels(geracao),tratamento="10casal"))
</span><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">print(contr,X=TRUE)
</span>glm model parameter contrast
Contrast S.E. Lower Upper t df Pr(>|t|)
-0.298869262 0.03278233 -0.36417501 -0.23356352 -9.12 75 0.0000
0.006271251 0.03351287 -0.06048982 0.07303232 0.19 75 0.8521
-0.103435587 0.03532313 -0.17380286 -0.03306831 -2.93 75 0.0045
0.049914391 0.03237891 -0.01458771 0.11441650 1.54 75 0.1274
Contrast coefficients:
(Intercept) tratamento1casal geracaog3 geracaog6 geracaog9
0 1 0 0 0
0 1 0 0 0
0 1 0 0 0
0 1 0 0 0
tratamento1casal:geracaog3 tratamento1casal:geracaog6 tratamento1casal:geracaog9
0 0 0
1 0 0
0 1 0
0 0 1
<span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">##
</span><span class="Apple-style-span" style="border-collapse: separate; color: rgb(0, 0, 0); font-family: Arial; font-style: normal; font-variant: normal; font-weight: normal; letter-spacing: normal; line-height: normal; orphans: 2; text-indent: 0px; text-transform: none; white-space: normal; widows: 2; word-spacing: 0px; font-size: medium;"><span class="Apple-style-span" style="font-family: Monospace; font-size: 13px; line-height: 17px; white-space: pre-wrap;"><pre tabindex="0" class="GD40030CLR" style="font-family: Monospace; font-size: 10pt ! important; outline-style: none; border-style: none; white-space: pre-wrap ! important; margin: 0px; line-height: 1.3;"><span class="GD40030COR ace_keyword" style="white-space: pre; color: blue;">> </span><span class="GD40030CCR ace_keyword" style="color: blue;">summary(m.comple)## Dando uma olhada no modelo
</span>
Call:
glm(formula = des.ov.mu ~ tratamento * geracao, family = "quasipoisson",
data = dados6)
Deviance Residuals:
Min 1Q Median 3Q Max
-0.38017 -0.09964 0.00000 0.03447 0.87147
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 2.09063 0.02250 92.934 < 2e-16 ***
tratamento1casal -0.29887 0.03278 -9.117 8.93e-14 ***
geracaog3 -0.15385 0.03229 -4.765 9.04e-06 ***
geracaog6 -0.15621 0.03313 -4.715 1.09e-05 ***
geracaog9 -0.05985 0.03230 -1.853 0.067820 .
tratamento1casal:geracaog3 0.30514 0.04688 6.509 7.62e-09 ***
tratamento1casal:geracaog6 0.19543 0.04819 4.055 0.000121 ***
tratamento1casal:geracaog9 0.34878 0.04608 7.570 7.83e-11 ***
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Null deviance: 9.1366 on 82 degrees of freedom
Residual deviance: 2.9802 on 75 degrees of freedom
AIC: NA
Number of Fisher Scoring iterations: 4</pre></span></span><span class="GD40030CCR ace_keyword" style="color: blue;">
Obrigado,
Alexandre
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