| Description |
xxxii, 646 pages : illustrations ; 24 cm ; cm |
| Contents |
Contents note continued: 1.3.8.Online resources for this book -- 1.4.Recommended resources and books -- 1.4.1.Getting started -- 1.4.2.Data management in Stata -- 1.4.3.Reproducing your results -- 1.4.4.Recommended Stata Press books -- 2.Descriptive statistics -- 2.1.Chapter overview -- 2.2.Using and describing the GSS dataset -- 2.3.One-way tabulations -- 2.4.Summary statistics -- 2.5.Summary statistics by one group -- 2.6.Two-way tabulations -- 2.7.Cross-tabulations with summary statistics -- 2.8.Closing thoughts -- 3.Basic inferential statistics -- 3.1.Chapter overview -- 3.2.Two-sample t tests -- 3.3.Paired sample t tests -- 3.4.One-sample t tests -- 3.5.Two-sample test of proportions -- 3.6.One-sample test of proportions -- 3.7.Chi-squared and Fisher's exact test -- 3.8.Correlations -- 3.9.Immediate commands -- 3.9.1.Immediate test of two means -- 3.9.2.Immediate test of one mean -- 3.9.3.Immediate test of two proportions -- 3.9.4.Immediate test of one proportion -- |
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Contents note continued: 11.2.4.Example 3: Power for a medium effect -- 11.2.5.Example 4: Power for a range of effect sizes -- 11.2.6.Example 5: For a given N, compute the effect size -- 11.2.7.Example 6: Compute effect sizes given unequal Ns -- 11.3.Power analysis for one-way ANOVA -- 11.3.1.Overview -- Hypothesis 1. Traditional therapy versus control -- Hypothesis 2: Optimism therapy versus control -- Hypothesis 3: Optimism therapy versus traditional therapy -- Summary of hypotheses -- 11.3.2.Example 7: Testing hypotheses 1 and 2 -- 11.3.3.Example 8: Testing hypotheses 2 and 3 -- 11.3.4.Summary -- 11.4.Power analysis for ANCOVA -- 11.4.1.Example 9: Using pretest as a covariate -- 11.4.2.Example 10: Using correlated variables as covariates -- 11.5.Power analysis for two-way ANOVA -- 11.5.1.Example 11: Replicating a two-by-two analysis -- 11.5.2.Example 12: Standardized simple effects -- 11.5.3.Example 13: Standardized interaction effect -- |
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Contents note continued: 11.5.4.Summary: Power for two-way ANOVA -- 11.6.Closing thoughts -- 12.Repeated measures designs -- 12.1.Chapter overview -- 12.2.Example 1: One-way within-subjects designs -- 12.3.Example 2: Mixed design with two groups -- 12.4.Example 3: Mixed design with three groups -- 12.5.Comparing models with different residual covariance structures -- 12.6.Example 1 revisited: Using compound symmetry -- 12.7.Example 1 revisited again: Using small-sample methods -- 12.8.An alternative analysis: ANCOVA -- 12.9.Closing thoughts -- 13.Longitudinal designs -- 13.1.Chapter overview -- 13.2.Example 1: Linear effect of time -- 13.3.Example 2: Interacting time with a between-subjects IV -- 13.4.Example 3: Piecewise modeling of time -- 13.5.Example 4: Piecewise effects of time by a categorical predictor -- 13.5.1.Baseline slopes -- 13.5.2.Treatment slopes -- 13.5.3.Jump at treatment -- 13.5.4.Comparisons among groups at particular days -- 13.5.5.Summary of example 4 -- |
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Contents note continued: 13.6.Closing thoughts -- 14.Simple and multiple regression -- 14.1.Chapter overview -- 14.2.Simple linear regression -- 14.2.1.Decoding the output -- 14.2.2.Computing predicted means using the margins command -- 14.2.3.Graphing predicted means using the marginsplot command -- 14.3.Multiple regression -- 14.3.1.Describing the predictors -- 14.3.2.Running the multiple regression model -- 14.3.3.Computing adjusted means using the margins command -- 14.3.4.Describing the contribution of a predictor -- One-unit change -- Multiple-unit change -- Milestone change in units -- One SD change in predictor -- Partial and semipartial correlation -- 14.4.Testing multiple coefficients -- 14.4.1.Testing whether coefficients equal zero -- 14.4.2.Testing the equality of coefficients -- 14.4.3.Testing linear combinations of coefficients -- 14.5.Closing thoughts -- 15.More details about the regress command -- 15.1.Chapter overview -- 15.2.Regression options -- |
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Contents note continued: 15.3.Redisplaying results -- 15.4.Identifying the estimation sample -- 15.5.Stored results -- 15.6.Storing results -- 15.7.Displaying results with the estimates table command -- 15.8.Closing thoughts -- 16.Presenting regression results -- 16.1.Chapter overview -- 16.2.Presenting a single model -- 16.3.Presenting multiple models -- 16.4.Creating regression tables using esttab -- 16.4.1.Presenting a single model with esttab -- 16.4.2.Presenting multiple models with esttab -- 16.4.3.Exporting results to other file formats -- 16.5.More commands for presenting regression results -- 16.5.1.outreg -- 16.5.2.outreg2 -- 16.5.3.xml_tab -- 16.5.4.coefplot -- 16.6.Closing thoughts -- 17.Tools for model building -- 17.1.Chapter overview -- 17.2.Fitting multiple models on the same sample -- 17.3.Nested models -- 17.3.1.Example 1: A simple example -- 17.3.2.Example 2: A more realistic example -- 17.4.Stepwise models -- 17.5.Closing thoughts -- |
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Contents note continued: 18.Regression diagnostics -- 18.1.Chapter overview -- 18.2.Outliers -- 18.2.1.Standardized residuals -- 18.2.2.Studentized residuals, leverage, Cook's D -- 18.2.3.Graphs of residuals, leverage, and Cook's D -- 18.2.4.DFBETAs and avplots -- 18.2.5.Running a regression with and without observations -- 18.3.Nonlinearity -- 18.3.1.Checking for nonlinearity graphically -- 18.3.2.Using scatterplots to check for nonlinearity -- 18.3.3.Checking for nonlinearity using residuals -- 18.3.4.Checking for nonlinearity using a locally weighted smoother -- 18.3.5.Graphing an outcome mean at each level of predictor -- 18.3.6.Summary -- 18.3.7.Checking for nonlinearity analytically -- Adding power terms -- Using factor variables -- 18.4.Multicollinearity -- 18.5.Homoskedasticity -- 18.6.Normality of residuals -- 18.7.Closing thoughts -- 19.Power analysis for regression -- 19.1.Chapter overview -- 19.2.Power for simple regression -- 19.3.Power for multiple regression -- |
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Contents note continued: 19.4.Power for a nested multiple regression -- 19.5.Closing thoughts -- 20.Common features of estimation commands -- 20.1.Chapter overview -- 20.2.Common syntax -- 20.3.Analysis using subsamples -- 20.4.Robust standard errors -- 20.5.Prefix commands -- 20.5.1.The by: prefix -- 20.5.2.The nestreg: prefix -- 20.5.3.The stepwise: prefix -- 20.5.4.The svy: prefix -- 20.5.5.The mi estimate: prefix -- 20.6.Setting confidence levels -- 20.7.Postestimation commands -- 20.8.Closing thoughts -- 21.Postestimation commands -- 21.1.Chapter overview -- 21.2.The contrast command -- 21.3.The margins command -- 21.3.1.The at() option -- 21.3.2.Margins with factor variables -- 21.3.3.Margins with factor variables and the at() option -- 21.3.4.The dydx() option -- 21.4.The marginsplot command -- 21.5.The pwcompare command -- 21.6.Closing thoughts -- 22.Stata data management commands -- 22.1.Chapter overview -- 22.2.Reading data into Stata -- 22.2.1.Reading Stata datasets -- |
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Contents note continued: 22.2.2.Reading Excel workbooks -- 22.2.3.Reading comma-separated files -- 22.2.4.Reading other file formats -- 22.3.Saving data -- 22.4.Labeling data -- 22.4.1.Variable labels -- 22.4.2.A looping trick -- 22.4.3.Value labels -- 22.5.Creating and recoding variables -- 22.5.1.Creating new variables with generate -- 22.5.2.Modifying existing variables with replace -- 22.5.3.Extensions to generate egen -- 22.5.4.Recode -- 22.6.Keeping and dropping variables -- 22.7.Keeping and dropping observations -- 22.8.Combining datasets -- 22.8.1.Appending datasets -- 22.8.2.Merging datasets -- 22.9.Reshaping datasets -- 22.9.1.Reshaping datasets wide to long -- 22.9.2.Reshaping datasets long to wide -- 22.10.Closing thoughts -- 23.Stata equivalents of common IBM SPSS Commands -- 23.1.Chapter overview -- 23.2.ADD FILES -- 23.3.AGGREGATE -- 23.4.ANOVA -- 23.5.AUTORECODE -- 23.6.CASESTOVARS -- 23.7.COMPUTE -- 23.8.CORRELATIONS -- 23.9.CROSSTABS -- 23.10.DATA LIST -- |
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Contents note continued: 23.11.DELETE VARIABLES -- 23.12.DESCRIPTIVES -- 23.13.DISPLAY -- 23.14.DOCUMENT -- 23.15.FACTOR -- 23.16.FILTER -- 23.17.FORMATS -- 23.18.FREQUENCIES -- 23.19.GET FILE -- 23.20.GET TRANSLATE -- 23.21.LOGISTIC REGRESSION -- 23.22.MATCH FILES -- 23.23.MEANS -- 23.24.MISSING VALUES -- 23.25.MIXED -- 23.26.MULTIPLE IMPUTATION -- 23.27.NOMREG -- 23.28.PLUM -- 23.29.PROBIT -- 23.30.RECODE -- 23.31.RELIABILITY -- 23.32.RENAME VARIABLES -- 23.33.SAVE -- 23.34.SELECT IF -- 23.35.SAVE TRANSLATE -- 23.36.SORT CASES -- 23.37.SORT VARIABLES -- 23.38.SUMMARIZE -- 23.39.T-TEST -- 23.40.VALUE LABELS -- 23.41.VARIABLE LABELS -- 23.42.VARSTOCASES -- 23.43.Closing thoughts |
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Contents note continued: 3.9.5.Immediate cross-tabulations -- 3.10.Closing thoughts -- 4.One-way between-subjects ANOVA -- 4.1.Chapter overview -- 4.2.Comparing two groups using a t test -- 4.3.Comparing two groups using ANOVA -- 4.3.1.Computing effect sizes -- 4.4.Comparing three groups using ANOVA -- 4.4.1.Testing planned comparisons using contrast -- 4.4.2.Computing effect sizes for planned comparisons -- 4.5.Estimation commands and postestimation commands -- 4.6.Interpreting confidence intervals -- 4.7.Closing thoughts -- 5.Contrasts for a one-way ANOVA -- 5.1.Chapter overview -- 5.2.Introducing contrasts -- 5.2.1.Computing and graphing means -- 5.2.2.Making contrasts among means -- 5.2.3.Graphing contrasts -- 5.2.4.Options with the margins and contrast commands -- 5.2.5.Computing effect sizes for contrasts -- 5.2.6.Summary -- 5.3.Overview of contrast operators -- 5.4.Compare each group against a reference group -- 5.4.1.Selecting a specific contrast -- |
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Contents note continued: 5.4.2.Selecting a different reference group -- 5.4.3.Selecting a contrast and reference group -- 5.5.Compare each group against the grand mean -- 5.5.1.Selecting a specific contrast -- 5.6.Compare adjacent means -- 5.6.1.Reverse adjacent contrasts -- 5.6.2.Selecting a specific contrast -- 5.7.Comparing with the mean of subsequent and previous levels -- 5.7.1.Comparing with the mean of previous levels -- 5.7.2.Selecting a specific contrast -- 5.8.Polynomial contrasts -- 5.9.Custom contrasts -- 5.10.Weighted contrasts -- 5.11.Pairwise comparisons -- 5.12.Closing thoughts -- 6.Analysis of covariance -- 6.1.Chapter overview -- 6.2.Example 1: ANCOVA with an experiment using a pretest -- 6.3.Example 2: Experiment using covariates -- 6.4.Example 3: Observational data -- 6.4.1.Model 1: No covariates -- 6.4.2.Model 2: Demographics as covariates -- 6.4.3.Model 3: Demographics, socializing as covariates -- |
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Contents note continued: 6.4.4.Model 4: Demographics, socializing, health as covariates -- 6.5.Some technical details about adjusted means -- 6.5.1.Computing adjusted means: Method 1 -- 6.5.2.Computing adjusted means: Method 2 -- 6.5.3.Computing adjusted means: Method 3 -- 6.5.4.Differences between method 2 and method 3 -- 6.5.5.Adjusted means: Summary -- 6.6.Closing thoughts -- 7.Two-way factorial between-subjects ANOVA -- 7.1.Chapter overview -- 7.2.Two-by-two models: Example 1 -- 7.2.1.Simple effects -- 7.2.2.Estimating the size of the interaction -- 7.2.3.More about interaction -- 7.2.4.Summary -- 7.3.Two-by-three models -- 7.3.1.Example 2 -- Simple effects -- Simple contrasts -- Partial interaction -- Comparing optimism therapy with traditional therapy -- 7.3.2.Example 3 -- Simple effects -- Partial interactions -- 7.3.3.Summary -- 7.4.Three-by-three models: Example 4 -- 7.4.1.Simple effects -- 7.4.2.Simple contrasts -- 7.4.3.Partial interaction -- |
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Contents note continued: 7.4.4.Interaction contrasts -- 7.4.5.Summary -- 7.5.Unbalanced designs -- 7.6.Interpreting confidence intervals -- 7.7.Closing thoughts -- 8.Analysis of covariance with interactions -- 8.1.Chapter overview -- 8.2.Example 1: IV has two levels -- 8.2.1.Question 1: Treatment by depression interaction -- 8.2.2.Question 2: When is optimism therapy superior? -- 8.2.3.Example 1: Summary -- 8.3.Example 2: IV has three levels -- 8.3.1.Questions 1a and 1b -- Question 1a -- Question 1b -- 8.3.2.Questions 2a and 2b -- Question 2a -- Question 2b -- 8.3.3.Overall interaction -- 8.3.4.Example 2: Summary -- 8.4.Closing thoughts -- 9.Three-way between-subjects analysis of variance -- 9.1.Chapter overview -- 9.2.Two-by-two-by-two models -- 9.2.1.Simple interactions by season -- 9.2.2.Simple interactions by depression status -- 9.2.3.Simple effects -- 9.3.Two-by-two-by-three models -- 9.3.1.Simple interactions by depression status -- |
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Contents note continued: 9.3.2.Simple partial interaction by depression status -- 9.3.3.Simple contrasts -- 9.3.4.Partial interactions -- 9.4.Three-by-three-by-three models and beyond -- 9.4.1.Partial interactions and interaction contrasts -- 9.4.2.Simple interactions -- 9.4.3.Simple effects and simple contrasts -- 9.5.Closing thoughts -- 10.Supercharge your analysis of variance (via regression) -- 10.1.Chapter overview -- 10.2.Performing ANOVA tests via regression -- 10.3.Supercharging your ANOVA -- 10.3.1.Complex surveys -- 10.3.2.Homogeneity of variance -- 10.3.3.Robust regression -- 10.3.4.Quantile regression -- 10.4.Main effects with interactions: anova versus regress -- 10.5.Closing thoughts -- 11.Power analysis for analysis of variance and covariance -- 11.1.Chapter overview -- 11.2.Power analysis for a two-sample t test -- 11.2.1.Example 1: Replicating a two-group comparison -- 11.2.2.Example 2: Using standardized effect sizes -- 11.2.3.Estimating effect sizes -- |
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Machine generated contents note: 1.Introduction -- 1.1.Read me first! -- 1.1.1.Downloading the example datasets and programs -- 1.1.2.Other user-written programs -- The fre command -- The esttab command -- The extremes command -- 1.2.Why use State -- 1.2.1.ANOVA -- 1.2.2.Supercharging your ANOVA -- 1.2.3.Stata is economical -- 1.2.4.Statistical powerhouse -- 1.2.5.Easy to learn -- 1.2.6.Simple and powerful data management -- 1.2.7.Access to user-written programs -- 1.2.8.Point and click or commands: Your choice -- 1.2.9.Powerful yet simple -- 1.2.10.Access to Stata source code -- 1.2.11.Online resources for learning Stata -- 1.2.12.And yet there is more! -- 1.3.Overview of the book -- 1.3.1.Part I: Warming up -- 1.3.2.Part II: Between-subjects ANOVA models -- 1.3.3.Part III: Repeated measures and longitudinal models -- 1.3.4.Part IV: Regression models -- 1.3.5.Part V: Stata overview -- 1.3.6.The GSS dataset -- 1.3.7.Language used in the book -- |
| Notes |
Formerly CIP. Uk |
| Bibliography |
Includes bibliographical references and index |
| SUBJECT |
Stata. http://id.loc.gov/authorities/names/n88156843
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| Subject |
Linear models (Statistics) -- Computer programs.
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Psychology -- Graphic methods -- Computer programs.
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Social sciences -- Graphic methods -- Computer programs.
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Psychology -- Statistical methods -- Computer programs.
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Social sciences -- Statistical methods -- Computer programs.
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Statistics -- Computer programs.
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| LC no. |
2015947163 |
| ISBN |
9781597181730 (paperback) |
