# Plot Points +/- Error Bars Creates plot showing user-specified points (e.g. means, medians, regression coefficients) along with user-specified error bars (e.g. standard deviations, min/max, 95% confidence intervals). ```r dots_bars(y = NULL, bars = NULL, bars.lower = y - bars, bars.upper = y + bars, truth = NULL, group.labels = NULL, group.dividers = TRUE, subgroup.spacing = 1, subgroup.labels = NULL, subgroup.pch = NULL, subgroup.col = NULL, points.list = NULL, arrows.list = NULL, xaxis.list = NULL, yaxis.list = xaxis.list, abline.dividers.list = NULL, abline.truth.list = NULL, legend.list = NULL, ...) ``` ## Arguments - `y`: Numeric vector of y-values for different groups, or numeric matrix where each column contains y-values for clustered subgroups within a group. - `bars`: Numeric vector or matrix (matching whichever type `y` is) specifying the length of the error bar for each group/subgroup (i.e. distance from point to one end of error bar). - `bars.lower`: Numeric vector or matrix (matching whichever type `y` is) specifying the position of the lower end of the error bar for each group/subgroup. - `bars.upper`: Numeric vector or matrix (matching whichever type `y` is) specifying the position of the upper end of the error bar for each group/subgroup. - `truth`: Numeric value specifying true value of parameter being estimated. If specified, a horizontal reference line is added to the plot. - `group.labels`: Character vector of labels for the groups. - `group.dividers`: Logical value for whether to add vertical lines distinguishing the groups. - `subgroup.spacing`: Numeric value controlling the amount of spacing between subgroups, with values > 1 corresponding to more spacing. - `subgroup.labels`: Character vector giving labels for the subgroups. - `subgroup.pch`: Plotting symbol for different subgroups within each group. - `subgroup.col`: Plotting color for different subgroups within each group. - `points.list`: Optional list of inputs to pass to `points`. - `arrows.list`: Optional list of inputs to pass to `arrows`. - `xaxis.list`: Optional list of inputs to pass to `axis` for x-axis. - `yaxis.list`: Optional list of inputs to pass to `axis` for y-axis. - `abline.dividers.list`: Optional list of inputs to pass to `abline` for group dividers. Only used if `group.dividers = TRUE`. - `abline.truth.list`: Optional list of inputs to pass to `abline` for horizontal line at true value of parameter. Only used if `truth` is specified. - `legend.list`: Optional list of inputs to pass to `legend`. - `...`: Additional arguments to pass to `plot` function. ## Returns Plot showing points +/- error bars across groups/subgroups. ## Examples ```r # Generate 100 values from normal distributions with different means, and # graph mean +/- standard deviation across groups dat <- cbind(rnorm(100, 2), rnorm(100, 2.5), rnorm(100, 1.75)) means <- apply(dat, 2, mean) sds <- apply(dat, 2, sd) fig1 <- dots_bars(y = means, bars = sds, main = "Mean +/- SD by Group", ylab = "Mean +/- SD") # Simulate BMI values for males and females in 3 different age groups, and # graph mean +/- 95% CI sex <- as.factor(c(rep("Male", 300), rep("Female", 300))) age <- as.factor(rep(c("Young", "Middle", "Old"), 2)) bmi <- c(rnorm(100, 25, 4), rnorm(100, 26, 4.25), rnorm(100, 27, 4.5), rnorm(100, 26.5, 4.5), rnorm(100, 27.25, 4.75), rnorm(100, 28, 5)) dat <- data.frame(sex = sex, age = age, bmi = bmi) means <- tapply(dat$bmi, dat[, c("sex", "age")], mean) ci.lower <- tapply(dat$bmi, dat[, c("sex", "age")], function(x) t.test(x)$conf.int[1]) ci.upper <- tapply(dat$bmi, dat[, c("sex", "age")], function(x) t.test(x)$conf.int[2]) fig2 <- dots_bars(y = means, bars.lower = ci.lower, bars.upper = ci.upper, main = "BMI by Sex and Age", ylab = "BMI (mean +/- CI)", xlab = "Age group") ```

dots_bars function