title: Get 95% confidence interval with glm(..) in R
body: <p>Here are some data</p>
  
  <pre><code>dat = data.frame(y = c(9,7,7,7,5,6,4,6,3,5,1,5), x = c(1,1,2,2,3,3,4,4,5,5,6,6), color = rep(c('a','b'),6))
  </code></pre>
  
  <p>and the plot of these data if you wish</p>
  
  <pre><code>require(ggplot)
  ggplot(dat, aes(x=x,y=y, color=color)) + geom_point() + geom_smooth(method='lm')
  </code></pre>
  
  <p>When running a model with the function <code>MCMCglmm()</code>…</p>
  
  <pre><code>require(MCMCglmm)
  summary(MCMCglmm(fixed = y~x/color, data=dat))
  </code></pre>
  
  <p>I get the lower and upper 95% interval for the estimate allowing me to know if the two slopes (color = a and color = b) are significantly different.</p>
  
  <p>When looking at this output...</p>
  
  <pre><code>summary(glm(y~x/color, data=dat))
  </code></pre>
  
  <p>... I can't see the confidence interval!</p>
  
  <p>My question is:</p>
  
  <p>How can I have these lower and upper 95% interval confidence for the estimates when using the function <code>glm()</code>?</p>