# Additional Plots and Stats with ggquickeda

#### Samer Mouksassi

#### 2024-09-12

Source:`vignettes/AdditionalPlotsStats.Rmd`

`AdditionalPlotsStats.Rmd`

In this vignette we will expand what we have learned in the Introduction to ggquickeda vignette.

### Multiple Y variables, recoding continuous variables to categories and Medina/PI:

This first section will illustrate how to use more than one y variable and how to generate a Median and a Ribbon showing a 95% Prediction interval (default) over the x variable (Time).

Using the built-in demo dataset:

- Change the mapped y variable(s) to Conc and Dose (ProTip: you can drag and drop the y variables to change their order)
- In the
**Categorize/cut**subtab select Age to be cut into three binned categories - In the
**Categorize/cut**subtab select Weight to be cut into three quantiles categories - Go to
**Color/Group/Split/Size/Fill Mappings**and map Colour By and Fill By to Age and Column Split to Weight the Extra Row split is automatically set to yvars since you have selected more than one y variable.

- Go to
**Median PIs**and select Median/PI and then you this get this plot:

We can see that Dose does not change over time and that the highest Age category is only present in the second and third weight categories (older subjects have higher weights).

### Boxplots, Median/PI, Mean:

- Remove all previous mappings from column split, colour by etc.
- Change the mapped y variable(s) to Weight and x variable to Age and remove Weight from Recode into Quantile Categories and select Age instead.
- Go to
**Points, Lines**and increase Point Size to 6 and make the transparency of the points equal to 0.1 - Explore the jitter position including the custom one
- Go to
**Color/Group/Split/Size/Fill**and map Color By:, Group By: Fill By: and Column Split: to Gender - Go to
**One Row by ID(s)**and select ID so we keep one row by ID

- Go To
**Median PI**and uncheck**Ignore Mapped Group**so the Median PI uses the mapped Gender Group By:. - Try to experiment what Label Values? and Label N? do Keep Label N? checked.
- Apply all the selected options in the screenshot

- Go to
**Boxplots**and check the Add a Boxplot? checkbox. - Go back to
**Median PI**and choose the PI to be 50% so it will be at the boxplot box edges. - Go to
**Boxplots**try to change the size of outliers and to remove the boxplot legend.

- Next go to the
**Mean (CI)**menu select Mean and check Show points and Force Mean(s) Shape (Diamond will be used by default) - Try to play with the various shapes options and or the size of the mean point(s).
- Check Label Values? and Check Ignore Mapped Color and choose Mean Label Geom as auto text repel.

### Continuous and categorical variables descriptive stats:

In the following part we will generate a descriptive stats table that reflect the plot that we just did and then add Race.

- Click on the
**Descriptive Stats**Tab - Map Extra Column Split to Gender and explore with the Flip the order of the columns checkbox
- Try to add more statistics in the Statistics to display for continuous variables
- Add Race to the y variable(s) to see the statistics for a categorical variable

### Univariate Plots:

Remove all y variable(s) and any column splits keeping Age as x variable gives a barplot since Age has been categorized.

Remove Age from Recode into Quantile Categories so it goes back to a
numeric variable and the generated distribution will be a density plot
instead of a barplot. Reapply the ID in **One Row by
ID(s)** as the data manipulation steps are sequential and
changing something in the first tab will reset the steps in the
subsequent ones.

Play with the options in the **Histograms/Density/Bar**
to see how they affect the generated plots.