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Michael Mitchell's A Visual Guide to Stata Graphics, Fourth Edition
provides an essential introduction and reference for Stata
graphics. The fourth edition retains the features that made the
first three editions so useful: A complete guide to Stata's graph
command Exhaustive examples of customized graphs Visual indexing of
features-just look for a picture that matches what you want to do
This edition includes new discussions of color, Unicode characters,
export formats, sizing of graph elements, and schemes. The section
on colors has been greatly expanded to include over 50 examples
that demonstrate how to modify colors, add transparency, and change
intensity. In the discussion of text modifications, Mitchell now
shows how to include Unicode characters such as Greek letters,
symbols, and emojis. New examples have also been added that show
how to change the size of graph elements such as text, markers, and
line widths using both absolute units (points, inches, and
centimeters) as well as relative units (line large or *2 for two
times the original size). Finally, the look of graphs throughout
the book has changed-most graphs are now created using a common
updated scheme. The book's visual style makes it easy to find
exactly what you need. A color-coded, visual table of contents runs
along the edge of every page and shows readers exactly where they
are in the book. You can see the color-coded chapter tabs without
opening the book, providing quick visual access to each chapter.
The heart of each chapter is a series of entries that are typically
formatted three to a page. Each entry shows a graph command (with
the emphasized portion of the command highlighted in red), the
resulting graph, a description of what is being done, and the
dataset used. Because every feature, option, and edit is
demonstrated with a graph, you can often flip through a section of
the book to find exactly the effect you are seeking. The book
begins with an introduction to Stata graphs that includes an
overview of graphs types, schemes, and options and the process of
building a graph. Then, it turns to detailed discussions of many
graph types-scatterplots, regression fit plots, line plots, contour
plots, bar graphs, box plots, and many others. Mitchell shows how
to create each type of graph and how to use options to control the
look of the graph. Because Stata's graph command will let you
customize any aspect of the graph, Mitchell spends ample time
showing you the most valuable options for obtaining the look you
want. If you are in a hurry to discover one special option, you can
skim the chapter until you see the effect you want and then glance
at the command to see what is highlighted in red. After focusing on
specific types of graphs, Mitchell undertakes an in-depth
presentation of the options available across almost all graph
types. This includes options that add and change the look of
titles, notes, and such; control the number of ticks on axes;
control the content and appearance of the numbers and labels on
axes; control legends; add and change the look of annotations;
graph over subgroups; change the look of markers and their labels;
size graphs and their elements; and more. To complete the graphical
journey, Mitchell discusses and demonstrates the 12 styles that
unite and control the appearance of the myriad graph objects. These
styles are angles, colors, clock positions, compass directions,
connecting points, line patterns, line widths, margins, marker
sizes, orientations, marker symbols, and text sizes. You won't want
to overlook the appendix in this book. There Mitchell first gives a
quick overview of the dozens of statistical graph commands that are
not strictly the subject of the book. Even so, these commands use
the graph command as an engine to draw their graphs; therefore,
almost all that Mitchell has discussed applies to them. He also
addresses combining graphs-showing you how to create complex and
multipart images from previously created graphs. In a crucial
section titled "Putting it all together", Mitchell shows us how to
do just that. We learn more about overlaying twoway plots, and we
learn how to combine data management and graphics to create plots
such as bar charts of rates with capped confidence intervals.
Mitchell concludes by warning us about mistakes that can be made
when typing graph commands and how to correct them. The fourth
edition of A Visual Guide to Stata Graphics is a complete guide to
Stata's graph command and the associated Graph Editor. Whether you
want to tame the Stata graph command, quickly find out how to
produce a graphical effect, or learn approaches that can be used to
construct custom graphs, this is the book to read.
This second edition of Data Management Using Stata focuses on tasks
that bridge the gap between raw data and statistical analysis. It
has been updated throughout to reflect new data management features
that have been added over the last 10 years. Such features include
the ability to read and write a wide variety of file formats, the
ability to write highly customized Excel files, the ability to have
multiple Stata datasets open at once, and the ability to store and
manipulate string variables stored as Unicode. Further, this new
edition includes a new chapter illustrating how to write Stata
programs for solving data management tasks. As in the original
edition, the chapters are organized by data management areas:
reading and writing datasets, cleaning data, labeling datasets,
creating variables, combining datasets, processing observations
across subgroups, changing the shape of datasets, and programming
for data management. Within each chapter, each section is a
self-contained lesson illustrating a particular data management
task (for instance, creating date variables or automating error
checking) via examples. This modular design allows you to quickly
identify and implement the most common data management tasks
without having to read background information first. In addition to
the "nuts and bolts" examples, author Michael Mitchell alerts users
to common pitfalls (and how to avoid them) and provides strategic
data management advice. This book can be used as a quick reference
for solving problems as they arise or can be read as a means for
learning comprehensive data management skills. New users will
appreciate this book as a valuable way to learn data management,
while experienced users will find this information to be handy and
time saving-there is a good chance that even the experienced user
will learn some new tricks.
Interpreting and Visualizing Regression Models Using Stata, Second
Edition provides clear and simple examples illustrating how to
interpret and visualize a wide variety of regression models.
Including over 200 figures, the book illustrates linear models with
continuous predictors (modeled linearly, using polynomials, and
piecewise), interactions of continuous predictors, categorical
predictors, interactions of categorical predictors, and
interactions of continuous and categorical predictors. The book
also illustrates how to interpret and visualize results from
multilevel models, models where time is a continuous predictor,
models with time as a categorical predictor, nonlinear models (such
as logistic or ordinal logistic regression), and models involving
complex survey data. The examples illustrate the use of the
margins, marginsplot, contrast, and pwcompare commands. This new
edition reflects new and enhanced features added to Stata, most
importantly the ability to label statistical output using value
labels associated with factor variables. As a result, output
regarding marital status is labeled using intuitive labels like
Married and Unmarried instead of using numeric values such as 1 and
2. All the statistical output in this new edition capitalizes on
this new feature, emphasizing the interpretation of results based
on variables labeled using intuitive value labels. Additionally,
this second edition illustrates other new features, such as using
transparency in graphics to more clearly visualize overlapping
confidence intervals and using small sample-size estimation with
mixed models. If you ever find yourself wishing for simple and
straightforward advice about how to interpret and visualize
regression models using Stata, this book is for you.
Stata for the Behavioral Sciences, by Michael Mitchell, is the
ideal reference for researchers using Stata to fit ANOVA models and
other models commonly applied to behavioral science data. Drawing
on his education in psychology and his experience in consulting,
Mitchell uses terminology and examples familiar to he reader as he
demonstrates how to fit a variety of models, how to interpret
results, how to understand simple and interaction effects, and how
to explore results graphically. Although this book is not designed
as an introduction to Stata, it is appealing even to Stata novices.
Throughout the text, Mitchell thoughtfully addresses any features
of Stata that are important to understand for the analysis at hand.
He also is careful to point out additional resources such as
related videos from Stata's YouTube channel. This book is an
easy-to-follow guide to analyzing data using Stata for researchers
in the behavioral sciences and a valuable addition to the bookshelf
of anyone interested in applying ANOVA methods to a variety of
experimental designs.
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