grafify5.1.0 package

Easy Graphs for Data Visualisation and Linear Models for ANOVA

ga_anova

ANOVA table from a generalised additive model (gam)

ga_model

Fit a generalised additive model (gam)

get_graf_colours

Get graf internal

graf_col_palette_default

Call grafify palettes for scale & fill functions

graf_col_palette

Call grafify palettes for scale & fill functions

graf_colours

List of hexcodes of colours in grafify palettes

graf_palettes

List of palettes available in grafify package

make_1way_data

Make one-way or two-way independent group or randomised block design d...

make_1way_rb_data

Make one-way or two-way independent group or randomised block design d...

make_2way_data

Make one-way or two-way independent group or randomised block design d...

make_2way_rb_data

Make one-way or two-way independent group or randomised block design d...

mixed_anova_slopes

ANOVA table from linear mixed effects analysis.

mixed_anova

ANOVA table from linear mixed effects analysis.

mixed_model_slopes

Model from a linear mixed effects model with varying slopes

mixed_model

Model from a linear mixed effects model

plot_3d_point_sd

Plot of mean & error bars for 1-way ANOVAs with matched shapes mapped ...

plot_3d_scatterbar

Plot a bar graph for 1-way ANOVAs with matched shapes mapped to blocki...

plot_3d_scatterbox

Plot a scatter and box plot for 1-way ANOVAs with matched shapes mappe...

plot_3d_scatterviolin

Plot a scatter with violin & box plot for 1-way ANOVAs with matched sh...

plot_4d_point_sd

Plot mean & error bars for 2-way ANOVAs with or without a blocking fac...

plot_4d_scatterbar

Plot scatter plot with bar & error bars for 2-way ANOVAs with or witho...

plot_4d_scatterbox

Plot scatter, box & whiskers for 2-way ANOVAs with or without a blocki...

plot_4d_scatterviolin

Plot scatter, box & violin for 2-way ANOVAs with or without a blocking...

plot_befafter_box

Before-after style graph with a boxplot

plot_befafter_colours

Plot a before-after plot with lines joining colour-matched symbols.

plot_befafter_shapes

Plot a before-after plot with lines joining shape-matched symbols.

plot_density

Plot density distribution of data.

plot_dotbar_sd

Plot a dotplot on a bar graph with SD error bars with two variables.

plot_dotbox

Plot a dotplot on a boxplot with two variables.

plot_dotviolin

Plot a dotplot on a violin plot with two variables.

plot_gam_predict

Plot prediction of gam model

plot_grafify_palette

See grafify colour palettes

plot_histogram

Plot data distribution as histograms.

plot_lm_predict

Plot data and predictions from linear model

plot_logscale

Add log transformations to graphs

plot_point_sd

Plot a point as mean with SD error bars using two variables.

plot_qq_gam

Plot model diagnostics for generalised additive models

plot_qqline

Plot quantile-quantile (QQ) graphs from data.

plot_qqmodel

Plot quantile-quantile (QQ) graphs from residuals of linear models.

plot_scatterbar_sd

Plot scatter dots on a bar graph with SD error bars with two variables...

plot_scatterbox

Plot a scatter plot on a boxplot with two variables.

plot_scatterviolin

Plot a scatter plot on a violin plot with two variables.

plot_xy_CatGroup

Plot points on a quantitative X - Y plot & a categorical grouping vari...

plot_xy_NumGroup

Plot points on a quantitative X - Y plot & a numeric grouping variable...

posthoc_Levelwise

Level-wise post-hoc comparisons from a linear or linear mixed effects ...

posthoc_Pairwise

Pairwise post-hoc comparisons from a linear or linear mixed effects mo...

posthoc_Trends_Levelwise

Use emtrends to get level-wise comparison of slopes from a linear mode...

posthoc_Trends_Pairwise

Use emtrends to get pairwise comparison of slopes from a linear model.

posthoc_Trends_vsRef

Use emtrends to get level-wise comparison of slopes from a linear mode...

posthoc_vsRef

Post-hoc comparisons to a control or reference group.

scale_colour_grafify

scale_colour_ and scale_fill_ functions

scale_fill_grafify

scale_colour_ and scale_fill_ functions

simple_anova

ANOVA table from a linear model fit to data.

simple_model

Model from a linear model fit to data.

table_summary

Get numeric summary grouped by factors

table_x_reorder

Reordering groups along X-axis

theme_grafify

A modified theme_classic() for grafify-like graphs.

Easily explore data by plotting graphs with a few lines of code. Use these ggplot() wrappers to quickly draw graphs of scatter/dots with box-whiskers, violins or SD error bars, data distributions, before-after graphs, factorial ANOVA and more. Customise graphs in many ways, for example, by choosing from colour blind-friendly palettes (12 discreet, 3 continuous and 2 divergent palettes). Use the simple code for ANOVA as ordinary (lm()) or mixed-effects linear models (lmer()), including randomised-block or repeated-measures designs, and fit non-linear outcomes as a generalised additive model (gam) using mgcv(). Obtain estimated marginal means and perform post-hoc comparisons on fitted models (via emmeans()). Also includes small datasets for practising code and teaching basics before users move on to more complex designs. See vignettes for details on usage <https://grafify.shenoylab.com/>. Citation: <doi:10.5281/zenodo.5136508>.