CONTENT

Learn how to communicate your data with Stata’s powerful graphics features. This course will introduce different kinds of graphs and demonstrate how to use them for exploratory data analysis. Topics include how to use graphs to check model assumptions; how to format, save, and export your graphs for publication using the Graph Editor; how to create custom graph schemes; how to create complex graphs by layering and combining multiple graphs; how to use margins and marginsplot; and more. Bonus material includes information on user-written graph commands and useful data management tools.

 

PREREQUISITES

Stata 16 installed and working.

Basic knowledge of using Stata interactively

Internet web browser, installed and working (course is platform independent)

 

PROGRAM

 

LESSON I: GETTING TO KNOW YOUR DATA USING GRAPHS

Introduction

Why graphs are an important tool for exploratory data analysis

Data management tools for graphing data

The example dataset

How to create and edit basic graphs using Stata

How to create and edit graphs with dialog boxes

How to edit graphs with the Graph Editor

How to create and edit graphs with commands

Some basic graphs

Graphs for one continuous variable

Graphs for one categorical variable

Graphs for two continuous variables

Graphs for two categorical variables

Graphs for one continuous and one categorical variable

Graphs for many variables

Storing, saving, and exporting graphs

Storing graphs in memory

Saving graphs to disk

Exporting graphs in .png format

Automating the process: Looping and saving

 

LESSON II: UNDERSTANDING YOUR RESULTS USING GRAPHS

Introduction

Model checking using graphs

Using the predict command

Checking model assumptions

Checking the normality assumption

Checking the linearity assumption

Checking the homoskedasticity assumption

Identifying outliers and influential observations

Visualizing the results of your models

Using the margins and marginsplot commands

A brief review of factor variables

Categorical independent variables

Multiple categorical independent variables

Continuous independent variables

Continuous and categorical independent variables

Average response versus response at average: The atmeans option

Contrasts of margin

Marginal effects: Margins of derivatives of responses

Using contour plots to visualize continuous-by-continuous interactions

 

LESSON III: FORMATTING GRAPHS FOR PUBLICATION

Introduction

Formatting titles, legends, and text boxes

Formatting titles

Formatting legends

Adding text boxes

Using italics, bold, superscripts, and subscripts

Using specialty characters

Using different fonts

Formatting numbers

Formatting axes, axis labels, ticks, gridlines, graph, and plot regions

Formatting categorical axis labels

Formatting the x and y axes

Formatting the x- and y-axis labels

Formatting major and minor ticks and gridlines

Adding reference lines

Formatting the graph and plot regions

Controlling the aspect ratio and size of graphs

Using schemes to change the overall look of graphs

Using built-in schemes

Defining your own schemes

Recording and saving edits in the Graph Editor

 

LESSON IV: ADVANCED GRAPHS: HOW TO LAYER AND COMBINE MULTIPLE GRAPHS

Introduction

Layering multiple graphs with the graph twoway command

Basic layered graphs with one y axis

Advanced layered graphs with one y axis

Basic layered graphs with two y axes

Advanced layered graphs with two y axes

Layering multiple graphs with the addplot() option

Basic

Advanced

Creating multiple graphs with the by() option

Combining different graphs with the graph combine command

Basics: Making a table of separate graphs

Advanced: Making a single complex graph from separate graphs

Exporting graphs for publication

Exporting graphs in pixel-based formats

Exporting graphs in vector-based formats

 

Note: The previous four lessons constitute the core material of the course. The following material is optional and introduces user-written graphic commands and useful data management tools.

 

Bonus material

Introduction

User-written graph commands

The Statistical Software Components (SSC) archive

The coefplot package by Ben Jann

How to write a simple graphics wrapper command

How to create animated graphs

Some fun graphs

How to create normal curves with shaded tails

How to show scatterplots with regression lines and residuals

How to add normal curves to regression lines

How to graph a histogram with a box plot

 

Appendix: Data management tools useful for graphing data

The destring and encode commands

The recode command

The tabulate command with the generate() option

The egen command

The contract and collapse commands

The statsby command

The snapshot command

The reshape command

Macros and loops

Extracting value labels to local macros

 

Note: There is a one-week break between the posting of Lessons 2 and 3; however, course leaders are available for discussion.