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A Gentle Introduction to Stata, Fourth Edition Alan C. Acock (Oregon State University, Corvallis, USA)

A Gentle Introduction to Stata, Fourth Edition By Alan C. Acock (Oregon State University, Corvallis, USA)

A Gentle Introduction to Stata, Fourth Edition by Alan C. Acock (Oregon State University, Corvallis, USA)


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A Gentle Introduction to Stata, Fourth Edition Summary

A Gentle Introduction to Stata, Fourth Edition by Alan C. Acock (Oregon State University, Corvallis, USA)

A Gentle Introduction to Stata, Fourth Edition is for people who need to learn Stata but who may not have a strong background in statistics or prior experience with statistical software packages. After working through this book, you will be able to enter, build, and manage a dataset, and perform fundamental statistical analyses. This book is organized like the unfolding of a research project. You begin by learning how to enter and manage data and how to do basic descriptive statistics and graphical analysis. Then you learn how to perform standard statistical procedures from t tests, nonparametric tests, and measures of association through ANOVA, multiple regression, and logistic regression. Readers who have experience with another statistical package may benefit more by reading chapters selectively and referring to this book as needed.

The fourth edition has incorporated numerous changes that were new with Stata 13. Coverage of the marginsplot command has expanded. This simplifies the construction of compelling graphs. There is a new chapter showing how to estimate path models using the sem (structural equation modeling) command. Menus have been updated, and several minor changes and corrections have been included based on suggestions from readers.

About Alan C. Acock (Oregon State University, Corvallis, USA)

Alan Acock is a sociologist and a University Distinguished Professor in the School of Social and Behavioral Health Sciences at Oregon State University. He held the Knudson Chair in Family Research and was also recognized as the Alumni Distinguished Professor based on his work with students. He is the author of Discovering Structural Equation Modeling Using Stata, Revised Edition. He has published more than 150 articles in leading journals across the social and behavioral sciences, including Structural Equation Modeling, Psychological Bulletin, Multivariate Behavioral Research, Journal of Gerontology, Journal of Adolescence, American Journal of Public Health, American Sociological Review, Journal of Marriage and Family, Social Forces, Drug and Alcohol Dependence, Educational and Psychological Measurement, Journal of Politics, Prevention Science, American Journal of Preventive Medicine, and many others. With this broad experience, Acock brings examples from a variety of disciplines.

Table of Contents

List of figures

List of tables

List of boxed tips

Preface

Support materials for the book

Getting started

Conventions

Introduction

The Stata screen

Using an existing dataset

An example of a short Stata session

Summary

Exercises

Entering data

Creating a dataset

An example questionnaire

Developing a coding system

Entering data using the Data Editor

The Variables Manager

The Data Editor (Browse) view

Saving your

Checking the data

Summary

Exercises

Preparing data for analysis

Introduction

Planning your work

Creating value labels

Reverse-code variables

Creating and modifying variables

Creating scales

Saving some of your data

Summary

Exercises

Working with commands, do-files, and results

Introduction

How Stata commands are constructed

Creating a do-file

Copying your results to a word processor

Logging your command file

Summary

Exercises

Descriptive statistics and graphs for one variable

Descriptive statistics and graphs

Where is the center of a distribution?

How dispersed is the distribution?

Statistics and graphs-unordered categories

Statistics and graphs-ordered categories and variables

Statistics and graphs-quantitative variables

Summary

Exercises

Statistics and graphs for two categorical variables

Relationship between categorical variables

Cross-tabulation

Chi-squared test

Percentages and measures of association

Odds ratios when dependent variable has two categories

Ordered categorical variables

Interactive tables

Tables-linking categorical and quantitative variables

Power analysis when using a chi-squared test of significance

Summary

Exercises

Tests for one or two means

Introduction to tests for one or two means

Randomization

Random sampling

Hypotheses

One-sample test of a proportion

Two-sample test of a proportion

One-sample test of means

Two-sample test of group means

Repeated-measures t test

Power analysis

Nonparametric alternatives

Summary

Exercises

Bivariate correlation and regression

Introduction to bivariate correlation and regression

Scattergrams

Plotting the regression line

An alternative to producing a scattergram, binscatter

Correlation

Regression

Spearman's rho: Rank-order correlation for ordinal data

Summary

Exercises

Analysis of variance

The logic of one-way analysis of variance

ANOVA example

ANOVA example using survey data

A nonparametric alternative to ANOVA

Analysis of covariance

Two-way ANOVA

Repeated-measures design

Intraclass correlation-measuring agreement

Power analysis with ANOVA

Power analysis for two-way ANOVA

Summary

Exercises

Multiple regression

Introduction to multiple regression

What is multiple regression?

The basic multiple regression command

Increment in R-squared: Semipartial correlations

Is the dependent variable normally distributed?

Are the residuals normally distributed?

Regression diagnostic statistics

Weighted data

Categorical predictors and hierarchical regression

A shortcut for working with a categorical variable

Fundamentals of interaction

Nonlinear relations

Power analysis in multiple regression

Summary

Exercises

Logistic regression

Introduction to logistic regression

An example

What is an odds ratio and a logit?

Data used in the rest of the chapter

Logistic regression

Hypothesis testing

More on interpreting results from logistic regression

Nested logistic regressions

Power analysis when doing logistic regression

Summary

Exercises

Measurement, reliability, and validity

Overview of reliability and validity

Constructing a scale

Reliability

Validity

Factor analysis

PCF analysis

But we wanted one scale, not four scales

Summary

Exercises

Working with missing values-multiple imputation

The nature of the problem

Multiple imputation and its assumptions about the mechanism for missingness

What variables do we include when doing imputations?

Multiple imputation

A detailed example

Summary

Exercises

The sem and gsem commands

Ordinary least-squares regression models using sem

A quick way to draw a regression model and a fresh start

The gsem command for logistic regression

Path analysis and mediation

Conclusions and what is next for the sem command

Exercises

What's next?

Introduction to the appendix

Resources

Summary

References

Author index

Subject index

Additional information

GOR013614943
9781597181426
1597181420
A Gentle Introduction to Stata, Fourth Edition by Alan C. Acock (Oregon State University, Corvallis, USA)
Used - Like New
Paperback
Stata Press
20140418
500
N/A
Book picture is for illustrative purposes only, actual binding, cover or edition may vary.
The book has been read, but looks new. The book cover has no visible wear, and the dust jacket is included if applicable. No missing or damaged pages, no tears, possible very minimal creasing, no underlining or highlighting of text, and no writing in the margins

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