<div dir="ltr"><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small">Boa noite pessoal</div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small"><br></div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small">Estou testando o pacote mice para fazer imputação múltipla de dados missing, conforme exemplo:</div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small"><br></div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small">library(mice)</div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small"><br></div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small"><div class="gmail_default">imp <- mice(nhanes2)</div><div class="gmail_default">fit <- with(imp, lm(chl~age+bmi))</div><div class="gmail_default"><br></div><div class="gmail_default">summary(fit)</div><div><br></div></div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small"><div>O resultado se resume em: </div><div><br></div><div><pre tabindex="0" class="gmail-GGHFMYIBMOB" id="gmail-rstudio_console_output" style="font-family:"ubuntu mono";outline:none;border:none;word-break:break-all;margin-top:0px;margin-bottom:0px;line-height:13.3333px;color:rgb(255,255,255);background-color:rgb(0,34,64);font-size:10.4pt;white-space:pre-wrap"> ## summary of imputation 1 :
Call:
lm(formula = chl ~ age + bmi)
Residuals:
Min 1Q Median 3Q Max
-46.37 -19.23 -11.24 12.66 83.69
Coefficients:
Estimate Std. Error t value Pr(>|t|)
(Intercept) 32.134 53.202 0.604 0.55232
age2 49.058 18.153 2.702 0.01334 *
age3 62.837 19.886 3.160 0.00472 **
bmi 4.907 1.795 2.733 0.01246 *
---
Signif. codes: 0 ‘***’ 0.001 ‘**’ 0.01 ‘*’ 0.05 ‘.’ 0.1 ‘ ’ 1
Residual standard error: 34.89 on 21 degrees of freedom
Multiple R-squared: 0.3835, Adjusted R-squared: 0.2954
F-statistic: 4.354 on 3 and 21 DF, p-value: 0.01557</pre></div></div><div><br></div><div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small">Eu gostaria de extrair o p-value: 0.01557 dessa estrutura, mas não consegui com os métodos convencionais, pois a estrutura parece diferente da estrutura gerada por um lm ou glm.</div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small"><br></div><div class="gmail_default" style="font-family:"times new roman",serif;font-size:small">Alguém poderia me ajudar</div><br></div>-- <br><div class="gmail_signature"><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div><div dir="ltr"><div dir="ltr"><div><font face="times new roman, serif"><i><span style="font-size:12.8px">In Jesu et Maria</span><br><br style="font-size:small"></i></font><div><div dir="ltr"><div dir="ltr"><div dir="ltr"><div style="font-size:small"><font face="times new roman, serif"><i>Obrigado</i></font></div><div style="font-size:small"><font face="times new roman, serif"><i>Prof. Elias Carvalho</i></font></div><div style="font-size:small"><font face="times new roman, serif"><i><br></i></font></div><div><font face="times new roman, serif" size="2"><i><div>"Felix, qui potuit rerum cognoscere causas" (Virgil 29 BC)</div><div>"Blessed is he who has been able to understand the cause of things"</div></i></font></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div></div>
</div>