A Gentle Introduction to Stata, Fifth Edition
Langue : anglais
Edité par Stata Press, 2016
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Alan C. Acock's A Gentle Introduction to Stata, Fifth Edition,is aimed at new Stata users who want to become proficient in Stata.After reading this introductory text, new users will be able not onlyto use Stata well but also to learn new aspects of Stata.Acock assumes that the user is not familiar with any statisticalsoftware. This assumption of a blank slate is central to the structureand contents of the book. Acock starts with the basics; for example,the portion of the book that deals with data management begins with acareful and detailed example of turning survey data on paper into aStata-ready dataset on the computer. When explaining how to go aboutbasic exploratory statistical procedures, Acock includes notes thatwill help the reader develop good work habits. This mixture ofexplaining good Stata habits and good statistical habits continuesthroughout the book.Acock is quite careful to teach the reader all aspects of using Stata.He covers data management, good work habits (including the use ofbasic do-files), basic exploratory statistics (including graphicaldisplays), and analyses using the standard array of basic statisticaltools (correlation, linear and logistic regression, and parametric andnonparametric tests of location and dispersion). He also successfullyintroduces some more advanced topics such as multiple imputation andstructural equation modeling in a very approachable manner. Acockteaches Stata commands by using the menus and dialog boxes while stillstressing the value of do-files. In this way, he ensures that alltypes of users can build good work habits. Each chapter has exercisesthat the motivated reader can use to reinforce the material.The tone of the book is friendly and conversational without ever beingglib or condescending. Important asides and notes about terminologyare set off in boxes, which makes the text easy to read without anyconvoluted twists or forward-referencing. Rather than splitting topicsby their Stata implementation, Acock arranges the topics as they wouldappear in a basic statistics textbook; graphics and postestimation arewoven into the material in a natural fashion. Real datasets, such asthe General Social Surveys from 2002 and 2006, are usedthroughout the book.The focus of the book is especially helpful for those in thebehavioral and social sciences because the presentation of basicstatistical modeling is supplemented with discussions of effect sizesand standardized coefficients. Various selection criteria, such assemipartial correlations, are discussed for model selection. Acockalso covers a variety of commands available for evaluating reliabilityand validity of measurements.The fifth edition of the book includes two new chapters that covermultilevel modeling and item response theory (IRT) models. Themultilevel modeling chapter demonstrates how to fit linear multilevelmodels using the mixed command. Acock discusses models withboth random intercepts and random coefficients, and he provides avariety of examples that apply these models to longitudinal data. TheIRT chapter introduces the use of IRT models for evaluating a set ofitems designed to measure a specific trait such as an attitude, value,or a belief. Acock shows how to use the irt suite of commands,which are new in Stata 14, to fit IRT models and to graph the results.In addition, he presents a measure of reliability that can be computedwhen using IRT.…
N° de réf. du vendeur CIN1597181854G
- Titre
- A Gentle Introduction to Stata, Fifth Edition
- Auteur
- Alan C Acock
- Éditeur
- Stata Press
- Année de publication
- 2016
- État de l'article
- Good
- Reliure
- Paperback
- Langue
- anglais
- ISBN à 10 chiffres
- 1597181854
- ISBN à 13 chiffres
- 9781597181853
- Édition
- 5ème Édition
Alan C. Acock's A Gentle Introduction to Stata, Fifth Edition,
is aimed at new Stata users who want to become proficient in Stata.
After reading this introductory text, new users will be able not only
to use Stata well but also to learn new aspects of Stata.
Acock assumes that the user is not familiar with any statistical
software. This assumption of a blank slate is central to the structure
and contents of the book. Acock starts with the basics; for example,
the portion of the book that deals with data management begins with a
careful and detailed example of turning survey data on paper into a
Stata-ready dataset on the computer. When explaining how to go about
basic exploratory statistical procedures, Acock includes notes that
will help the reader develop good work habits. This mixture of
explaining good Stata habits and good statistical habits continues
throughout the book.
Acock is quite careful to teach the reader all aspects of using Stata.
He covers data management, good work habits (including the use of
basic do-files), basic exploratory statistics (including graphical
displays), and analyses using the standard array of basic statistical
tools (correlation, linear and logistic regression, and parametric and
nonparametric tests of location and dispersion). He also successfully
introduces some more advanced topics such as multiple imputation and
structural equation modeling in a very approachable manner. Acock
teaches Stata commands by using the menus and dialog boxes while still
stressing the value of do-files. In this way, he ensures that all
types of users can build good work habits. Each chapter has exercises
that the motivated reader can use to reinforce the material.
The tone of the book is friendly and conversational without ever being
glib or condescending. Important asides and notes about terminology
are set off in boxes, which makes the text easy to read without any
convoluted twists or forward-referencing. Rather than splitting topics
by their Stata implementation, Acock arranges the topics as they would
appear in a basic statistics textbook; graphics and postestimation are
woven into the material in a natural fashion. Real datasets, such as
the General Social Surveys from 2002 and 2006, are used
throughout the book.
The focus of the book is especially helpful for those in the
behavioral and social sciences because the presentation of basic
statistical modeling is supplemented with discussions of effect sizes
and standardized coefficients. Various selection criteria, such as
semipartial correlations, are discussed for model selection. Acock
also covers a variety of commands available for evaluating reliability
and validity of measurements.
The fifth edition of the book includes two new chapters that cover
multilevel modeling and item response theory (IRT) models. The
multilevel modeling chapter demonstrates how to fit linear multilevel
models using the mixed command. Acock discusses models with
both random intercepts and random coefficients, and he provides a
variety of examples that apply these models to longitudinal data. The
IRT chapter introduces the use of IRT models for evaluating a set of
items designed to measure a specific trait such as an attitude, value,
or a belief. Acock shows how to use the irt suite of commands,
which are new in Stata 14, to fit IRT models and to graph the results.
In addition, he presents a measure of reliability that can be computed
when using IRT.
« Synopsis » peut appartenir à une autre édition de cet ouvrage.
Présentation de l'éditeur
Alan C. Acock's A Gentle Introduction to Stata, Fifth Edition,
is aimed at new Stata users who want to become proficient in Stata.
After reading this introductory text, new users will be able not only
to use Stata well but also to learn new aspects of Stata.
Acock assumes that the user is not familiar with any statistical
software. This assumption of a blank slate is central to the structure
and contents of the book. Acock starts with the basics; for example,
the portion of the book that deals with data management begins with a
careful and detailed example of turning survey data on paper into a
Stata-ready dataset on the computer. When explaining how to go about
basic exploratory statistical procedures, Acock includes notes that
will help the reader develop good work habits. This mixture of
explaining good Stata habits and good statistical habits continues
throughout the book.
Acock is quite careful to teach the reader all aspects of using Stata.
He covers data management, good work habits (including the use of
basic do-files), basic exploratory statistics (including graphical
displays), and analyses using the standard array of basic statistical
tools (correlation, linear and logistic regression, and parametric and
nonparametric tests of location and dispersion). He also successfully
introduces some more advanced topics such as multiple imputation and
structural equation modeling in a very approachable manner. Acock
teaches Stata commands by using the menus and dialog boxes while still
stressing the value of do-files. In this way, he ensures that all
types of users can build good work habits. Each chapter has exercises
that the motivated reader can use to reinforce the material.
The tone of the book is friendly and conversational without ever being
glib or condescending. Important asides and notes about terminology
are set off in boxes, which makes the text easy to read without any
convoluted twists or forward-referencing. Rather than splitting topics
by their Stata implementation, Acock arranges the topics as they would
appear in a basic statistics textbook; graphics and postestimation are
woven into the material in a natural fashion. Real datasets, such as
the General Social Surveys from 2002 and 2006, are used
throughout the book.
The focus of the book is especially helpful for those in the
behavioral and social sciences because the presentation of basic
statistical modeling is supplemented with discussions of effect sizes
and standardized coefficients. Various selection criteria, such as
semipartial correlations, are discussed for model selection. Acock
also covers a variety of commands available for evaluating reliability
and validity of measurements.
The fifth edition of the book includes two new chapters that cover
multilevel modeling and item response theory (IRT) models. The
multilevel modeling chapter demonstrates how to fit linear multilevel
models using the mixed command. Acock discusses models with
both random intercepts and random coefficients, and he provides a
variety of examples that apply these models to longitudinal data. The
IRT chapter introduces the use of IRT models for evaluating a set of
items designed to measure a specific trait such as an attitude, value,
or a belief. Acock shows how to use the irt suite of commands,
which are new in Stata 14, to fit IRT models and to graph the results.
In addition, he presents a measure of reliability that can be computed
when using IRT.
« A propos de ce titre » peut appartenir à une autre édition de cet ouvrage.
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