Teaching plan for the course unit

(Short version)


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General information


Course unit name: Social Research Techniques III

Course unit code: 360920

Academic year: 2021-2022

Coordinator: Jose Luis Condom Bosch

Department: Department of Sociology

Credits: 6

Single program: S



Estimated learning time

Total number of hours 150


Face-to-face and/or online activities



-  Lecture with practical component





-  Group tutorial





-  IT-based class




Supervised project


Independent learning




Learning objectives


Referring to knowledge

Overall goal
This course provides students with the fundamental tools for undertaking the statistical description of relations to facilitate a sociological understanding of both explanatory and causal models of social reality. It introduces various advanced statistical techniques for use in explanatory/causal sociological analysis for understanding social phenomena. Sociological statistical analysis is thus at the heart of the process of building theories.

Knowledge-related objectives
— Understand the logic and the process of analyses of both explanatory and causal models in sociology.
— Know how to use multivariate explanatory and causal analysis techniques based on the nature of the variables.
— Recognize and apply different types of control variables.
— Understand the approach, both sociologically and as regards interpretation, of multivariate explanatory analysis.
— Know how to construct and analyse explanatory and causal models.
— Know how to conduct comparative analyses.
— Be familiar with the general linear model.


Referring to abilities, skills

— Propose and test a theoretical model.
— Know how to interpret and write a report based on a multivariate analysis.
— Know how to work with the IBM SPSS computer program.
— Know how to use secondary data to test theoretical models.
— Know how to use and apply relevant analytical techniques to construct, analyse and interpret explanatory and causal models.
— Know how to use indices and typologies in causal analysis.
— Know how to compare groups and subpopulations in explanatory analyses of data.



Teaching blocks


1. The logic of causal analysis

*  The logic of sociological analysis requires the study of the causal research process. The role of empirical analysis in the theoretical advancement of the discipline. Maximizing impact when presenting research results.

1.1. The logic of sociological analysis 

1.2. From theory to practice 

2. The identification of causality

*  The identification of causality begins with an exploration of the types of relationship. Identification of possible spurious relationships and their analysis. The study of causality begins with contingency tables and is completed with correlation analysis.

2.1. Causal and spurious relationships: identification 

2.2. Typology of control variables

3. Analysis of relationships between variables

*  Methods for studying relationships between variables. The analysis of variance. Use of normal and hierarchical multiple regression, and logistic regression for the study of additive, linear causal models. Construction, testing and improvement of models.

3.1. Three-level contingency tables

3.2. Correlation and partial correlation

3.3. Multiple linear regression 

3.4. Logistic regression 

4. Causal analysis

*  Analysis of complex causal models by means of path analysis, model building, testing and improvement.

4.1. Model testing

4.2. Path analysis

4.3. Hierarchical models





Reading and study resources

Consulteu la disponibilitat a CERCABIB


Hayes, Andrew F. (2018) Introduction to mediation, moderation, and conditional process analysis : a regression-based approach, Nueva york, The Guilford Press

Catāleg UB  Enllaç

AGRESTI, Alan. Categorical Data Analysis. Nueva York : Wiley, 2002

Catāleg UB  Enllaç

ASHER, Herbert B. Causal Modeling. California : Sage, 1983

Catāleg UB  Enllaç

BERRY, William Dale; FELDMAN, Stanley. Multiple regression in practice. Newbury Park (Calif.): Sage, 1985

Catāleg UB  Enllaç

CEA D’ANCONA, María Angeles. Análisis Multivariable. Teoría y práctica en la investigación social. Madrid: Síntesis, 2002

Catāleg UB  Enllaç

DÍEZ MEDRANO, Juan. Métodos de análisis causal. Madrid: CIS, 1992

Catāleg UB  Enllaç

GUILLEN, Mauro F. Análisis de regresión múltiple. Madrid: CIS, 1992

Versiķ en línia (2a ed., 2014)  Enllaç

HELLEVIK, Ottar.  Introduction to Causal Analysis. Oslo : Norwegian University Press, 1988

Catāleg Col.lectiu Universitats Catalanes  Enllaç

JOVELL, Albert J. Análisis de regresión logística. CIS : Madrid, 1995

Catāleg UB  Enllaç

SÁNCHEZ CARRIÓN, Juan Javier. Análisis de tablas de contingencia. Madrid: CIS/Siglo XXI, 1989

Catāleg UB  Enllaç

SÁNCHEZ CARRIÓN, Juan Javier (ed.) Introducción a las técnicas de análisis multivariable. Madrid: CIS, 1984

STEVENS, James Paul. Applied multivariate statistics for the social sciences. New York, Routledge, 2009

VISAUTA VINACUA, Bienvenido. Técnicas de investigación social: Modelos Causales. Barcelona: Hispano Europea, 1986

Electronic text

IBM® SPSS® Statistics 21 (2012)

IBM SPSS Advanced Statistics
IBM SPSS Categories
IBM SPSS Custom Tables
IBM SPSS Data Preparation
IBM SPSS Regression
IBM SPSS Statistics Base
IBM SPSS Statistics Brief Guide
IBM SPSS Statistics Core System User’s Guide
 En línea [consulta: 14 de juliol de 2017] Disponible a: <