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Forest-Plot-Style Confidence Interval Display

Source: R/plot_ci.R
plot_ci.Rd

Creates a clean visualization of one or more effect size estimates with their confidence intervals.

Usage

plot_ci(
  ci = NULL,
  estimate = NULL,
  lower = NULL,
  upper = NULL,
  names = NULL,
  n = NULL,
  conf_level = 0.95,
  show_n = TRUE,
  reference_line = NULL,
  xlab = "Effect Size",
  title = NULL,
  palette = "okabe_ito"
)

Arguments

ci

A data.frame from a DMAR ci_* function. When supplied, the function auto-detects the format and extracts the point estimate(s), lower limit(s), and upper limit(s). Explicit estimate, lower, and upper arguments override values parsed from ci.

estimate

Numeric vector of point estimates.

lower

Numeric vector of lower confidence limits.

upper

Numeric vector of upper confidence limits.

names

Optional character vector of labels for each effect.

n

Optional numeric vector (or scalar) of sample sizes. Recycled to match the number of effects.

conf_level

Confidence level; used only for the axis label (default 0.95).

show_n

Logical. If TRUE (the default), the sample size is annotated above each estimate, with the estimate and its interval printed below.

reference_line

Optional numeric value at which to draw a vertical reference line (e.g., 0 for mean differences, 1 for ratios).

xlab

Label for the horizontal (effect size) axis. Defaults to "Effect Size".

title

Optional plot title.

palette

Character string naming the color palette. The point estimates and interval bars are drawn in the palette's primary color. Defaults to "okabe_ito", base R's colorblind-safe Okabe-Ito palette; "tableau" is also available.

Value

A ggplot2 object.

Details

The function accepts either (a) a data.frame produced by an DMAR ci_* function (e.g., ci_smd, ci_R2, ci_omega_squared), or (b) explicit numeric vectors for the estimate(s), lower bound(s), and upper bound(s).

The function recognizes three DMAR output formats:

Long term/value with estimate row

Output from ci_smd, which includes a row for the point estimate (e.g., term = "smd") in addition to "lower_limit" and "upper_limit".

Long term/value without estimate

Output from ci_R or ci_R2, which contains only "lower_limit" and "upper_limit". Supply the point estimate via the estimate argument.

Wide per-effect format

Output from ci_omega_squared, which has one row per effect with columns for the point estimate, lower_limit, upper_limit, and N.

Note

Requires ggplot2 (listed in Suggests).

See also

ci_smd, ci_R, ci_R2, ci_omega_squared, plot_smd, plot_R2

Other plotting: plot_R2(), plot_cfa_k(), plot_equivalence(), plot_forest(), plot_irt_information(), plot_mediation_mbco(), plot_randomization_test(), plot_regions_of_significance(), plot_smd(), plot_trajectories(), plot_trajectories_fitted(), power_equivalence_md_plot()

Author

Ken Kelley kkelley@nd.edu

Examples

# From explicit values.
plot_ci(estimate = 0.45, lower = 0.15, upper = 0.75,
        names = "Cohen's d", n = 60, reference_line = 0)


# From ci_smd() output.
ci_result <- ci_smd(smd = 0.5, n_1 = 50, n_2 = 50)
plot_ci(ci_result, n = 100, reference_line = 0)


# Multiple effects from ci_omega_squared(): the expectancy treatment
# and the grade classification in the pygmalion data.
pyg <- pygmalion
pyg$grade <- factor(pyg$grade)
fit <- aov(iq_8 ~ treatment + grade, data = pyg)
omega_result <- ci_omega_squared(fit)
plot_ci(omega_result, reference_line = 0,
        xlab = expression(omega^2))