r effect estimate plot as error bars by group

My goal is to create a plot showing effect estimates for 4 different levels of a categorical variable X grouped based on a grouping variable M1 like this. This example below has 5 levels for each variable but my X has 4 levels

enter image description here

Suppose this is my test dataset with effect estimates

effect_data <- data.frame(
  Level = factor(rep(1:4, each = 12)),  # Assuming 12 sets of analyses
  EffectEstimate = runif(48, min = -2, max = 2),  # Replace with your actual effect estimates
  LowerCI = runif(48, min = -3, max = -1),  # Replace with your actual lower CIs
  UpperCI = runif(48, min = 1, max = 3),  # Replace with your actual upper CIs
  M1  = factor(rep(letters[1:12], times = 4))
)

My plot ends up looking like this

# Plot the effect estimate as a bar chart
ggplot(effect_data, aes(x = Level, y = EffectEstimate)) +
  geom_bar(stat = "identity", position = "dodge", width = 0.7, fill = "blue") +
  geom_errorbar(aes(ymin = LowerCI, ymax = UpperCI), position = position_dodge(0.7), width = 0.25) +
  coord_flip() +
  facet_grid(.~Level)+
  labs(
    title = "Effect Estimates with Confidence Intervals",
    x = "Results from 12 different Models",
    y = "Effect Estimate"
  ) +
  theme_minimal()

This is not what I want, I am trying to generate a plot like the one above , any help is much appreciated. Thanks.

enter image description here

>Solution :

effect_data <- data.frame(
  Level = factor(rep(1:4, each = 12)),
  # Assuming 12 sets of analyses
  EffectEstimate = runif(48, min = -2, max = 2),
  # Replace with your actual effect estimates
  LowerCI = runif(48, min = -3, max = -1),
  # Replace with your actual lower CIs
  UpperCI = runif(48, min = 1, max = 3),
  # Replace with your actual upper CIs
  M1  = factor(rep(letters[1:12], times = 4))
)

From your description I am not sure what you are looking.
Here are two variants. Maybe one of them is what you desire?

library(tidyverse)

# Variant A
ggplot(effect_data,
       aes(
         x = Level,
         y = EffectEstimate,
         group = M1,
         fill = M1
       )) +
  geom_errorbar(aes(ymin = LowerCI, ymax = UpperCI),
                position = position_dodge(0.7),
                width = 0.25) +
  labs(title = "Effect Estimates with Confidence Intervals",
       x = "Results from 12 different Models",
       y = "Effect Estimate") +
  geom_bar(stat = "identity",
           position = "dodge",
           width = 0.7) +
  theme_minimal()



# Variant B
ggplot(effect_data,
       aes(
         x = M1,
         y = EffectEstimate,
         group = Level,
         fill = Level
       )) +
  geom_errorbar(aes(ymin = LowerCI, ymax = UpperCI),
                position = position_dodge(0.7),
                width = 0.25) +
  labs(title = "Effect Estimates with Confidence Intervals",
       x = "Results from 12 different Models",
       y = "Effect Estimate") +
  geom_bar(stat = "identity",
           position = "dodge",
           width = 0.7) +
  theme_minimal()

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