tm_g_ci.md
In teal.modules.clinical: 'teal' Modules for Standard Clinical Outputs

1. and 2. Mean and 95% CIs for mean

Code
  res
Output
  {
      plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
          y = AVAL, color = SEX, lty = SEX, shape = SEX)) + ggplot2::stat_summary(fun.data = stat_mean_ci, 
          geom = "errorbar", width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::stat_summary(fun = mean, geom = "point", position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::labs(title = "Confidence Interval Plot by Treatment Group", 
              caption = "Mean and 95% CIs for mean are displayed.", 
              x = "Treatment Group", y = "Value", color = "", lty = "", 
              shape = "")
  }

3. Confidence Interval Plot (using different stratification variable)

Code
  res
Output
  {
      plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
          y = AVAL, color = STRATA2, lty = STRATA2, shape = STRATA2)) + 
          ggplot2::stat_summary(fun.data = stat_mean_ci, geom = "errorbar", 
              width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::stat_summary(fun = mean, geom = "point", position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::labs(title = "Confidence Interval Plot by Treatment Group", 
              caption = "Mean and 95% CIs for mean are displayed.", 
              x = "Treatment Group", y = "Value", color = "", lty = "", 
              shape = "")
  }

4. Median and 95% CIs for median

Code
  res
Output
  {
      plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
          y = AVAL, color = STRATA1, lty = STRATA1, shape = STRATA1)) + 
          ggplot2::stat_summary(fun.data = stat_median_ci, geom = "errorbar", 
              width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::stat_summary(fun = median, geom = "point", position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::labs(title = "Confidence Interval Plot by Treatment Group", 
              caption = "Median and 95% CIs for median are displayed.", 
              x = "Treatment Group", y = "Value", color = "", lty = "", 
              shape = "")
  }

5. Using different alpha level

Code
  res
Output
  {
      plot <- ggplot2::ggplot(data = ANL, mapping = ggplot2::aes(x = ARMCD, 
          y = AVAL, color = SEX, lty = SEX, shape = SEX)) + ggplot2::stat_summary(fun.data = function(x) stat_mean_ci(x, 
          conf_level = 0.9), geom = "errorbar", width = 0.1, position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::stat_summary(fun = mean, geom = "point", position = ggplot2::position_dodge(width = 0.5)) + 
          ggplot2::labs(title = "Confidence Interval Plot by Treatment Group", 
              caption = "Mean and 90% CIs for mean are displayed.", 
              x = "Treatment Group", y = "Value", color = "", lty = "", 
              shape = "")
  }