RESM6011 Applied Research Methods (ARM):Correlational Methods
Topics to be covered will include: • the strengths and weaknesses of correlational designs, • how to construct a questionnaire, • psychometrics in classical test theory (including reliability, validity, sensitivity, specificity, principal components analysis and exploratory factor analysis), • correlation analysis, • linear regression (OLS; simple and multiple) and logistic regression (binary and multinomial), • extensions to regression using mediation and moderation. Sessions will be structured to enable an understanding of the appropriate use of and assumptions relating to analyses, the recommended sample size to ensure sufficient power for a given effect size, a step-by-step guide to carrying out analyses in SPSS, interpreting SPSS output, and how to report results. Alignment with Research Development Framework (RDF) Sub domain A1 (Knowledge base): Transferable skills acquired (RDF employability lens): Knowledge of: •The methods and techniques appropriate for research design •Literacy and numeracy skills and language abilities appropriate for research Behaviour: •Identifies, applies and develops methods and techniques appropriate for research projects Alignment with Research Development Framework (RDF) Sub domain A2 (Cognitive abilities): Transferable skills acquired (RDF employability lens): Behaviour: •Analyses and evaluates findings using appropriate methods •Recognises and validates problems; formulates and applies solutions to a range of research problems
Aims and Objectives
The purpose of this module is to refresh and build upon statistical knowledge and skills acquired during undergraduate research methods training.This correlational methods module is divided into six three hour interactive sessions that cover relevant methodological concepts used in applied psychology and hands-on experience using SPSS.
Having successfully completed this module you will be able to:
- critically evaluate the strengths and limitations of correlational research designs.
- evaluate whether the use of correlational techniques is appropriate.
- apply relevant factors in operationalising variables and designing questionnaires.
- demonstrate practical skills in psychometric evaluation of the reliability and validity of questionnaire data
- apply and report correlational techniques appropriately, with specific reference to: Applying parametric assumptions and data checking requirements, sample size calculations, carrying out relevant analyses using SPSS, Interpreting and communicating results of analyses at a professional level
1. Correlational designs and questionnaire development 2. Bivariate correlation, partial correlation, and non-parametric correlation. 3. Principal component analysis and exploratory factor analysis 4. Linear (OLS) Regression (simple and multiple) & Logistic regression (binary and multinomial) 5. Interactions in regression: Moderation analysis 6. Simple path analysis using regression: Mediation analysis
This module is one of a series of Applied Research Methods (APM) modules developed within the Academic Unit of Psychology. These modules are taught by experts in applied psychology and have been developed to build upon research methods training already completed at undergraduate level and cover the common needs for training in research methods, and quantitative and qualitative analyses for all students in their first year of postgraduate study in psychology. The modules have been designed to contribute towards both the content areas and levels of expertise required to meet the academic knowledge base requirements and required competencies for Programme Standards set out by the British Psychological Society (BPS), and the Standards of Proficiency for Practioner Psychologists set out by the Health and Care Professions Council (HCPC). This module includes a step-by-step guide to carrying out the tests using the statistical software SPSS.
Learning and Teaching
Teaching and learning methods
This is a 10 CATS (5 ECTS) module, which translates into a total study time of 100 hours. These 100 hours are split into 18 teaching hours and 82 hours of independent study. The 18 teaching hours will consist of six sessions, each lasting 3 hours. Sessions will comprise a lecture directly followed by a computer workshop during which you will be able to gain hands-on experience using the techniques described in the lecture, and give you the opportunity to reinforce your learning from lectures and independent study. Where possible, the lectures will follow an interactive format through the use of zappers. During the computer workshops you will complete tasks on blackboard using SPSS. Tasks can be completed in collaboration with your peers, and with support from teaching assistants. The module assumes a level of prior knowledge of statistical methods and SPSS equivalent to that provided during an undergraduate degree in Psychology.
|Total study time||100|
Resources & Reading list
Clark-Carter, D (2010). Quantitative Psychological Research.
Mayers, A (2013). Introduction to statistics and SPSS in Psychology.
Blackboard. A variety of relevant e-learning resources will be available on Blackboard. These will include lecture slides and additional materials, computer workshop tasks, datasets for analysis, reading lists, links to journal articles, and links to useful websites.
Marks, D. F. & Yardley, L. (2004). Research methods for clinical and health psychology.
Aiken, L. S., & West, S. G. (1991). Multiple regression: Testing and interpreting interactions.
Field, A. (2013). Discovering Statistics Using SPSS.
SPSS. You will require access to SPSS, which is available on the University’s computer workstations and can be downloaded to your own computer for use during your studies. This is available through iSolutions: https://www.software.soton.ac.uk/
Howitt, D & Cramer, D. (2014). Introduction to Research Methods in Psychology.
APA (2010). Publication Manual of the American Psychological Association.
Hayes A F (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach.
Tabachnick, B.G. & Fidell L.S. (2014). Using Multivariate Statistics.
Howitt D. & Cramer D. (2014). An introduction to statistics in psychology.
|Assignment (1500 words)||70%|
|Individual multiple questions ()||30%|
Repeat type: Internal & External