
Analysis of questionnaire data with R
Title:
Analysis of questionnaire data with R
Author:
Falissard, Bruno.
ISBN:
9781439817667
Personal Author:
Publication Information:
Boca Raton, Fla. ; London : Chapman & Hall/CRC, c2012.
Physical Description:
ix, 269 p. : ill. ; 25 cm.
General Note:
Formerly CIP.
Contents:
Machine generated contents note: 1.1.About Questionnaires -- 1.2.Principles of Analysis -- 1.2.1.Overviews -- 1.2.2.Specific Aspects of Questionnaire Data Analysis -- 1.3.The Mental Health in Prison (MHP) Study -- 1.4.If You Are a Complete R Beginner -- 1.4.1.First Steps -- 1.4.2.Functions from Optional Packages -- 1.4.3.When Assistance Is Needed -- 1.4.4.Importing a Dataset -- 1.4.5.More about the R Language -- 2.1.Description Using Summary Statistics -- 2.2.Summary Statistics in Subgroups -- 2.3.Histograms -- 2.4.Boxplots -- 2.5.Barplots -- 2.6.Pie Charts -- 2.7.Evolution of a Numerical Variable across Time (Temperature Diagram) -- 3.1.Relative Risks and Odds Ratios -- 3.2.Correlation Coefficients -- 3.3.Correlation Matrices -- 3.4.Cartesian Plots -- 3.5.Hierarchical Clustering -- 3.6.Principal Component Analysis -- 3.7.A Spherical Representation of a Correlation Matrix -- 3.8.Focused Principal Component Analysis -- 4.1.Confidence Interval of a Proportion --
Contents note continued: 4.2.Confidence Interval of a Mean -- 4.3.Confidence Interval of a Relative Risk or an Odds Ratio -- 4.4.Statistical Tests of Hypothesis: Comparison of Two Percentages -- 4.5.Statistical Tests of Hypothesis: Comparison of Two Means -- 4.6.Statistical Tests of Hypothesis: Correlation Coefficient -- 4.7.Statistical Tests of Hypothesis: More than Two Groups -- 4.8.Sample Size Requirements: Survey Perspective -- 4.9.Sample Size Requirements: Inferential Perspective -- 5.1.Linear Regression Models for Quantitative Outcomes -- 5.2.Logistic Regression for Binary Outcome -- 5.3.Logistic Regression for a Categorical Outcome with More than Two Levels -- 5.4.Logistic Regression for an Ordered Outcome -- 5.5.Regression Models for an Outcome Resulting from a Count -- 6.1.Coding Numerical Predictors -- 6.2.Coding Categorical Predictors -- 6.3.Choosing Predictors -- 6.4.Interaction Terms -- 6.5.Assessing the Relative Importance of Predictors --
Contents note continued: 6.6.Dealing with Missing Data -- 6.7.Bootstrap -- 6.8.Random Effects and Multilevel Modelling -- 7.1.Item Analysis (1): Distribution -- 7.2.Item Analysis (2): The Multi-Trait Multi-Method Approach to Confirm a Subscale Structure -- 7.3.Assessing the Unidimensionality of a Set of Items -- 7.4.Factor Analysis to Explore the Structure of a Set of Items -- 7.5.Measurement Error (1): Internal Consistency and the Cronbach Alpha -- 7.6.Measurement Error (2): Inter-Rater Reliability -- 8.1.Linear Regression as a Particular Instance of Structural Equation Modelling -- 8.2.Factor Analysis as a Particular Instance of Structural Equation Modelling -- 8.3.Structural Equation Modelling in Practice -- 9.1.Importing and Exporting Datasets -- 9.2.Manipulation of Datasets -- 9.3.Manipulation of Variables -- 9.4.Checking Inconsistencies -- A.1.Data Manipulations -- A.1.1.Importation/Exportation of Datasets -- A.1.2.Manipulation of Datasets --
Contents note continued: A.1.3.Manipulation of Variables -- A.2.Descriptive Statistics -- A.2.1.Univariate -- A.2.2.Bivariate -- A.2.3.Multidimensional -- A.3.Statistical Inference -- A.4.Statistical Modelling -- A.5.Validation of a Composite Score.