# Black & White Figures for Print Journals

#### Daniel Lüdecke

#### 2025-07-10

This document shows examples how to create b/w figures, e.g. if you don’t want colored figures for print-journals.

## Barplots in grey-scaled colors

There are two ways to create plots in black and white or greyscale. For bar plots, `geom.colors = "gs"` creates a plot using a greyscale (based on `scales::grey_pal()`).

    library(sjPlot)
    library(sjmisc)
    library(sjlabelled)
    library(ggplot2)
    theme_set(theme_bw())
    data(efc)
    plot_grpfrq(efc$e42dep, efc$c172code, geom.colors = "gs")

## Lineplots in b/w with different linetypes

Similar to barplots, lineplots - mostly from `plot_model()` - can be plotted in greyscale as well (with `colors = "gs"`). However, in most cases lines colored in greyscale are difficult to distinguish. In this case, `plot_model()` supports black & white figures with different linetypes. Use `colors = "bw"` to create a b/w-plot.

    # create binrary response
    y <- ifelse(efc$neg_c_7 < median(na.omit(efc$neg_c_7)), 0, 1)

    # create data frame for fitting model
    df <- data.frame(
      y = to_factor(y),
      sex = to_factor(efc$c161sex),
      dep = to_factor(efc$e42dep),
      barthel = efc$barthtot,
      education = to_factor(efc$c172code)
    )

    # set variable label for response
    set_label(df$y) <- "High Negative Impact"

    # fit model
    fit <- glm(y ~., data = df, family = binomial(link = "logit"))

    # plot marginal effects
    plot_model(
      fit,
      type = "pred",
      terms = c("barthel", "sex","dep"),
      colors = "bw",
      ci.lvl = NA
    )

Different linetypes do not apply to all linetyped plots, if these usually only plot a single line - so there’s no need for different linetypes, and you can just set `colors = "black"` (or `colors = "bw"`).

    # plot coefficients
    plot_model(fit, colors = "black")