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List of tables | |
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List of figures | |
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Preface | |
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Support materials for the book | |
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Getting started | |
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Conventions | |
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Introduction | |
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The Stata screen | |
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Using an existing dataset | |
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An example of a short Stata session | |
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Summary | |
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Exercises | |
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Entering data | |
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Creating a dataset | |
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An example questionnaire | |
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Developing a coding system | |
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Entering data using the Data Editor | |
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Value labels | |
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The Variables Manager | |
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The Data Editor (Browse) view | |
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Saving your dataset | |
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Checking the data | |
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Summary | |
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Exercises | |
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Preparing data for analysis | |
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Introduction | |
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Planning your work | |
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Creating value labels | |
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Reverse-code variables | |
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Creating and modifying variables | |
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Creating scales | |
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Saving some of your data | |
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Summary | |
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Exercises | |
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Working with commands, do-files, and results | |
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Introduction | |
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How Stata commands are constructed | |
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Creating a do-file | |
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Copying your results to a word processor | |
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Logging your command file | |
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Summary | |
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Exercises | |
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Descriptive statistics and graphs for one variable | |
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Descriptive statistics and graphs | |
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Where is the center of a distribution? | |
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How dispersed is the distribution? | |
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Statistics and graphs unordered categories | |
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Statistics and graphs ordered categories and variables | |
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Statistics and graphs quantitative variables | |
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Summary | |
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Exercises | |
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Statistics and graphs for two categorical variables | |
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Relationship between categorical variables | |
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Cross-tabulation | |
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Chi-squared test | |
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Degrees of freedom | |
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Probability tables | |
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Percentages and measures of association | |
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Odds ratios when dependent variable has two categories | |
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Ordered categorical variables | |
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Interactive tables | |
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Tables linking categorical and quantitative variables | |
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Power analysis when using a chi-squared test of significance | |
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Summary | |
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Exercises | |
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Tests for one or two means | |
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Introduction to tests for one or two means | |
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Randomization | |
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Random sampling | |
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Hypotheses | |
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One-sample test of a proportion | |
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Two-sample test of a proportion | |
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One-sample test of means | |
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Two-sample test of group means | |
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Testing for unequal variances | |
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Repeated-measures t test | |
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Power analysis | |
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Nonparametric alternatives | |
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Mann-Whitney two-sample rank-sum test | |
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Nonparametric alternative: Median test | |
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Summary | |
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Exercises | |
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Bivariate correlation and regression | |
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Introduction to bivariate correlation and regression | |
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Scattergrams | |
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Plotting the regression line | |
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Correlation | |
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Regression | |
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Spearman's rho: Rank-order correlation for ordinal data | |
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Summary | |
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Exercises | |
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Analysis of variance | |
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The logic of one-way analysis of variance | |
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ANOVA example | |
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ANOVA example using survey data | |
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A nonparametric alternative to ANOVA | |
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Analysis of covariance | |
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Two-way ANOVA | |
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Repeated-measures design | |
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Intraclass correlation measuring agreement | |
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Summary | |
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Exercises | |
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Multiple regression | |
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Introduction to multiple regression | |
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What is multiple regression? | |
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The basic multiple regression command | |
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Increment in R-squared: Semipartial correlations | |
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Is the dependent variable normally distributed? | |
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Are the residuals normally distributed? | |
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Regression diagnostic statistics | |
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Outliers and influential cases | |
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Influential observations: DFbeta | |
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Combinations of variables may cause problems | |
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Weighted data | |
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Categorical predictors and hierarchical regression | |
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A shortcut for working with a categorical variable | |
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Fundamentals of interaction | |
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Power analysis in multiple regression | |
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Summary | |
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Exercises | |
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Logistic regression | |
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Introduction to logistic regression | |
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An example | |
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What is an odds ratio and a logit? | |
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The odds ratio | |
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The logit transformation | |
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Data used in the rest of the chapter | |
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Logistic regression | |
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Hypothesis testing | |
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Testing individual coefficients | |
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Testing sets of coefficients | |
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Nested logistic regressions | |
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Power analysis when doing logistic regression | |
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Summary | |
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Exercises | |
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Measurement, reliability, and validity | |
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Overview of reliability and validity | |
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Constructing a scale | |
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Generating a mean score for each person | |
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Stability and test-retest reliability | |
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Equivalence | |
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Split-half and alpha reliability internal consistency | |
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Kuder-Richardson reliability for dichotomous items | |
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Rater agreement kappa (�) | |
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Validity | |
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Expert judgment | |
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Criterion-related validity | |
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Construct validity | |
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Factor analysis | |
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PCF analysis | |
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Orthogonal rotation: Varimax | |
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Oblique rotation: Promax | |
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But we wanted one scale, not four scales | |
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Scoring our variable | |
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Summary | |
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Exercises | |
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Working with missing values multiple imputation | |
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The nature of the problem | |
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Multiple imputation and its assumptions about the mechanism for missingness | |
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What variables do we include when doing imputations? | |
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Multiple imputation | |
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A detailed example | |
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Preliminary analysis | |
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Setup and multiple-imputation stage | |
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The analysis stage | |
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For those who want an R<sup>2</sup> and standardized �s | |
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When impossible values are imputed | |
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Summary | |
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Exercises | |
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What's next? | |
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Introduction to the appendix | |
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Resources | |
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Web resources | |
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Books about Stata | |
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Short courses | |
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Acquiring data | |
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Summary | |
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References | |
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Author index | |
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Subject index | |