Publisher:

Chapman & Hall/CRC

Number of Pages:

269

Price:

89.95

ISBN:

9781439817667

Date Received:

Thursday, October 20, 2011

Reviewable:

No

Reviewer Email Address:

Publication Date:

2011

Format:

Hardcover

Audience:

Category:

Textbook

**Introduction**About Questionnaires

Principles of Analysis

The Mental Health in Prison (MHP) Study

If You Are a Complete R Beginner

Description of Responses

Description using "Summary Statistics"

Summary Statistics in Subgroups

Histograms

Boxplots

Barplots

Pie Charts

Evolution of a Numerical Variable across Time (Temperature Diagram)

Description of Relationships between Variables

Relative Risks and Odds-Ratios

Correlation Coefficients

Correlation Matrices

Cartesian Plots

Hierarchical Clustering

Principal Component Analysis

A Spherical Representation of a Correlation Matrix

Focused Principal Component Analysis

Confidence Intervals and Statistical Tests of Hypothesis

Confidence Interval of a Proportion

Confidence Interval of a Mean

Confidence Interval of a Relative Risk or an Odds-Ratio

Statistical Tests of Hypothesis: Comparison of Two Percentages

Statistical Tests of Hypothesis: Comparison of Two Means

Statistical Tests of Hypothesis: The Correlation Coefficient

Statistical Tests of Hypothesis: More than Two Groups

Sample Size Requirements: The Survey Perspective

Sample Size Requirement: The Inferential Perspective

Introduction to Linear, Logistic, Poisson, and Other Regression Models

Linear Regression Models for Quantitative Outcomes

Logistic Regression for Binary Outcome

Logistic Regression for a Categorical Outcome with More than Two Levels

Logistic Regression for an Ordered Outcome

Regression Models for an Outcome Resulting from a Count

About Statistical Modelling

Coding Numerical Predictors

Coding Categorical Predictors

Choosing Predictors

Interaction Terms

Assessing the Relative Importance of Predictors

Dealing with Missing Data

The Bootstrap

Random Effects and Multilevel Modelling

Principles for the Validation of a Composite Score

Item Analysis (1): Distribution

Item Analysis (2): The Multi trait Multi-method Approach to Confirm a Subscale Structure

Assessing the Unidimensionality of a Set of Items

Factor Analysis to Explore the Structure of a Set of Items

Measurement Error (1): Internal Consistency and the Cronbach Alpha

Measurement Error (2): Inter-rater Reliability

8 Introduction to Structural Equation Modelling

Linear Regression as a Particular Instance of Structural

Equation Modelling

Factor Analysis as a Particular Instance of Structural

Equation Modelling

Structural Equation Modelling in Practice

Introduction to Data Manipulation using R

Importing and Exporting Datasets

Manipulation of Datasets

Manipulation of Variables

Checking Inconsistencies

Appendix A: The Analysis of Questionnaire Data using R: Memory Card

Data Manipulations

Importation Exportation of Datasets

Manipulation of Datasets

Manipulation of Variables

Descriptive Statistics

Univariate

Bivariate

Multidimensional

Statistical Inference

Statistical Modelling

Validation of a Composite Score

Publish Book:

Modify Date:

Tuesday, January 17, 2012

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