QMSBR
Quantitative Methods for Social and Behavioral Research
A modular collection for quantitative courses
Understand quantitative studies and carry out your own analyses
QMSBR—Quantitative Methods for Social and Behavioral Research—is a modular collection of chapters designed to support various quantitative and statistical courses. Its modular design serves several courses at once: each course chooses its own route through one canonical set of chapters whose identities and links stay stable, so a correction to a chapter improves every route that uses it. The chapters help readers make sense of quantitative studies, following how a study turns a question into evidence and a bounded answer. They also help readers carry out analyses in which design, statistical reasoning, interpretation, and reproducible computing stay connected.
The material is organized in parts. Each part opens with a short introduction, keeps a concept reference to consult while reading, and presents its chapters in reading order. Part One covers foundations, regression, and generalized linear models; Part Two covers factor analysis and structural equation modeling. The R support pages run R in the browser, with nothing to install.
To start, read a part introduction and then its first chapter.
Part One: Introduction, Concept Reference, and Chapters 1–9 · Part Two: Introduction, Concept Reference, and Chapters 1–4 · Argument Chapters A and B · R support for Part One Chapters 3 and 4
Collections
Part One
Foundations, Regression, and Generalized Linear Models
- Introduction PDF
- Concept Reference PDF
- 1. The Quantitative Research Journey PDF
- 2. Data, Distributions, and Variation PDF
- 3. Estimates, Uncertainty, and Statistical Tests PDF
- 4. Group Comparisons with Analysis of Variance PDF
- 5. Description and Basic Inference with R PDF
- 6. Group Comparisons and Statistical Modelling with R PDF
- 7. Simple Linear Regression PDF
- 8. Multiple Regression I: Conditioning, Checks, and Coordinated Questions PDF
- 9. Multiple Regression II: Categorical Predictors, Model Comparison, Nonlinearity, and Robust Uncertainty PDF
Part Two
Factor Analysis and Structural Equation Modeling
Part Three
Multilevel and Longitudinal Models
Not yet available
Part Three is reserved for data with a nested or repeated structure: multilevel models for units grouped inside classes, schools, or sites, and longitudinal models for the same units measured more than once. It is not yet available.
R support
Practice R in the browser, nothing to install
Argument Approach
Reading a study as a question–answer contract
Not yet available
C. Arguments involving latent variables or an additional measurement layer
The argument chapters extend the approach. No numbered chapter depends on them.
Using QMSBR in a course
Each course chooses its own route and sequence through the chapters. A course system such as Moodle holds the term schedule, announcements, classroom notes, and assessment, while this site holds the chapters themselves and carries no course-specific material. Chapter identities and links stay stable, so a course can cite a chapter page and rely on reaching the current version of it. Using QMSBR in a course, on the About page, sets out the division in more detail.
How to use this site
Read online, or download the PDF. Every chapter, introduction, and concept reference can be read online or downloaded as a PDF, and both are built from the same source. The web page adds a responsive layout, a table of contents, search, and selectable code; the PDF suits printing and annotation. The PDF link sits beside each page’s title in the collections above.
Keep the concept reference open while reading. Each part gathers its central concepts, symbols, and notation in a concept reference. Read a chapter for the lesson, and open the concept reference when you meet a term or a symbol and want its meaning and the chapter that explains it.
Try an analysis on the R support pages. The R support pages carry a live R session in the browser, so you can run a chapter’s analysis, change it, and see what changes without installing anything. The data sources page says where each dataset comes from and on what terms it can be reused.
Read the argument-based approach the chapters share. The chapters read a quantitative study as a question, the evidence and reasons that support an answer, and the limits of that answer. The Argument-Based Approach summarizes this reading, and Part One Chapter 1 develops it in full.
What comes next
Part One, Chapters 10–14
Not yet available
Part One continues into interaction and moderation, generalized linear models, prediction, and causal design. The introduction and concept reference describe the full collection; the numbered chapters currently available on this site are Chapters 1–9.
Part Two, Chapters 5–12
Not yet available
Part Two continues from confirmatory factor analysis into observed and latent structural models, causal identification, conditional relationships, group comparisons, incomplete records, growth and study planning.
Part Three
Not yet available
Part Three is reserved for multilevel and longitudinal models.
Argument Chapter C
Not yet available
Arguments involving latent variables or an additional measurement layer will examine how measurement assumptions and interpretations support a substantive answer.