A comprehensive dataset for demonstrating advanced forest plot functionality. Contains multiple variable types (continuous, categorical, hierarchical), multi-model comparisons, sample sizes, and color grouping information.
Format
A data frame with 33 rows and 15 columns:
- variable
Character vector of variable names and group headers
- est
Numeric vector of effect estimates (Model 1 or single model)
- lower
Numeric vector of lower confidence limits (Model 1)
- upper
Numeric vector of upper confidence limits (Model 1)
- pval
Numeric vector of p-values (Model 1)
- est_2
Numeric vector of effect estimates for Model 2 (NA for single-model rows)
- lower_2
Numeric vector of lower confidence limits for Model 2
- upper_2
Numeric vector of upper confidence limits for Model 2
- pval_2
Numeric vector of p-values for Model 2
- est_3
Numeric vector of effect estimates for Model 3
- lower_3
Numeric vector of lower confidence limits for Model 3
- upper_3
Numeric vector of upper confidence limits for Model 3
- pval_3
Numeric vector of p-values for Model 3
- n_total
Numeric vector of total sample sizes
- n_event
Numeric vector of event counts
- event_pct
Numeric vector of event percentages
- color_id
Character vector of color group identifiers for visualization
- note
Character vector of notes and model descriptions
Details
This dataset demonstrates various forest plot scenarios:
Continuous variables (Age, BMI)
Categorical variables with subgroups (Sex, BMI category, Treatment)
Multi-level hierarchical structures
Multi-model comparisons (Models 1-3 for last 3 rows)
Sample size and event information
Color grouping for enhanced visualizations