MRes Psychological Research Methods Module list Modules may include: Advanced Experimentation and Statistics (One) Advanced Experimentation and Statistics One examines the theoretical and philosophical underpinnings of statistics used in experimental research (e.g., statistical inference, power and effect size). The framework for the module is a regression/glm approach to statistics that focuses on the relationship between multiple linear regression, ANOVA and ANCOVA. The module also covers application of these concepts in widely available computer software such as SPSS and the relationship between different experimental designs (e.g., factorial designs, multi-stage sampling, RCTs, cross-sectional designs, longitudinal designs or single-case studies) and statistical issues such as power and generalizability. Practical issues such as dealing with violations of statistical assumptions or missing data are also considered. The course will cover both the conceptual basis of the analytic techniques and the practical application of them (e.g., using SPSS or R). Allied topics such as statistical inference, power and effect size will be covered. Qualitative Research Design and Analysis (One) This module will provide you with a comprehensive philosophical and methodological grounding in qualitative research. The mains aims of the module are to: Outline the main philosophical/epistemological arguments supporting the use of qualitative research methods in psychology. Outline the key issues, problems, and new insights that shape qualitative research design in psychology. Familiarise students with a range of data collection techniques used by qualitative researchers in psychology. 1
Develop student s capacity to manage and handle qualitative data. Familiarise students with a range of data analytic techniques used by qualitative researchers in psychology (and to outline the differences between them). Further develop students ability to report, present, and evaluate qualitative research. Module content: Philosophical and epistemological introduction to qualitative research (the limitations of the scientific method and the main alternatives to this philosophy and method). Qualitative research design issues (reflexivity, reliability, validity, ethical issues). Data gathering techniques (written texts, focus groups, diary methods, interviews, etc.). Data handling, organization, and management techniques (processes of transcription and coding, relevant computer packages, etc.). Data analysis techniques (content analysis, thematic analysis; grounded theory; interpretative phenomenological analysis; conversation analysis; discourse analysis). Psychometrics (One): Developing Psychometric Scales in Research and Practice This module will provide you with a comprehensive knowledge of psychometric theory and how this theory can be applied to the different stages of test development. More specifically the module aims to: Provide an understanding of basic psychometric principles that underpin measurement in psychology. Demonstrate the process of test development through practical application of theory. Allow students to accurately appraise the quality of test instruments used in psychological research. This module will provide you with an understanding of psychometric theory and the processes involved in developing a new measure. The following are areas that are likely to be covered: Classical model of test error. Reliability. Validity. Item and factor analytic methods of test construction. Developing and pretesting items. Questionnaire design and formatting. Scale transformations and norms. 2
Research and Professional Skills This module will introduce you to a range of key research and research dissemination skills necessary for the pursuit of an academic or professional career in psychology. The main aim of the module will be to ensure that you are capable of planning, carrying out, and seeking funding for ethically sound, independent research projects in a psychological setting, and that you are able to present the results of that research in a variety of media for both professional and non-professional audiences. The module will also focus on the development of skills to enhance employability and ensure you are equipped to best present yourself to prospective employers both within and outside of psychology. The following are areas that are likely to be covered: Literature searching and reviewing. Critical thinking. Ethics and ethics applications. Preparing a grant application. Collaborative research. Writing papers for publication. Poster presentations. Oral presentations. Personal development plans. Applications & CVs. Observational Methods This module will provide you with a knowledge of, and practical skills in, observational methods. More specifically the module aims to: Develop understanding of the use of different observational methods to address psychological questions Demonstrate the processes involved in the coding and analysis of observational data Enable students to conduct a piece of observational research Allow students to appraise critically the quality of observational designs and address issues concerning relating to reliability and validity To develop students abilities to handle observational data To further develop students abilities to report, present and evaluate observational designs and data The module aims to provide specialist training in observational methods. Topics may include: Observational research designs (the use of structured and un-structured observations) Quasi-experimental techniques Data gathering techniques 3
Advantages and disadvantages of observational designs Data handling, organisation, and management techniques Developing valid and reliable coding schemes and the application of these coding schemes to analyse video material Reliability and validity MRes Psychological Research Project This module will enable students to develop and demonstrate professional psychological research skills appropriate to the discipline by: Designing (including addressing ethical issues) and undertaking an independent research project in psychology, using an advanced research method of their own choice, under the guidance of an appropriate supervisor. Critically assessing methodological issues and choosing and applying an appropriate method. Gaining practice in using and interpreting advanced statistical and other analyses to a professional standard. Developing skills associated with the writing and structuring of professional quality research reports. Demonstrating advanced scholarship and a critical awareness of current research. Regular supervision will be provided to guide students research projects. Supervisory support will be provided as students plan and prepare their project proposals (e.g., advanced research skills and use of specialist equipment) and afterwards at regular intervals. Students need to choose two from the following four modules: Advanced Experimentation and Statistics Two Advanced Experimentation and Statistics Two uses the regression framework adopted in Advanced Experimentation and Statistics Two and introduces additional advanced statistical topics such as logistic regression, Poisson regression, meta-analysis and multilevel modeling. The module builds on practical topics introduced in Advanced Experimentation & Statistics One such as dealing with violations of assumptions and the limitations of standard research designs for real world data (e.g., handling unbalanced or missing data in repeated measures analyses). The module also introduces you to specialist statistical software such as R or MLwiN. The course will cover both the conceptual basis of the analytic techniques and the practical application of them (e.g., using SPSS or R). The main topics will be applications of applied regression, models for repeated measures data (e.g., repeated measures ANOVA or multilevel models), and applied generalized linear models (e.g., logistic regression, loglinear models or Poisson regression). 4
Psychometrics (Two): Using Psychometric Scales in Research and Practice This module progresses from Psychometrics One, to illustrate how psychometric theory can be applied to the design of high quality survey research. The module aims to provide you with an understanding of the uses of measurement within different areas of psychology. You will need to demonstrate a knowledge of the survey design and methodology, including analysis and interpretation of survey data. More specifically the module aims to: Provide an understanding of the application of psychological testing. Provide an understanding of design issues in survey-based research within psychology. Explore methodological issues relating to administration of psychological measures. Examine the analysis and interpretation of data obtained from survey research. This module will provide you with an understanding of the issues relating to the use of psychological measures within psychology. The following are areas that are likely to be covered: Use of psychological tests within different areas of psychology. Methods of test administration. Research approaches and scale selection. Qualifications and publishing rights. Ethical issues in psychological testing. Analysis and interpretation of scale data. Critical evaluation of literature using survey based methods. Qualitative Research Design and Analysis Two This module will provide you with both the theoretical underpinnings and analytic practice of conversation analysis (CA), membership categorisation (MCA) and discursive psychology (DP). The main aims of the module are to: Outline the theoretical background of CA, MCA and DP and situate within the wider field of discourse research. Develop student s understanding of the research process associated with CA, MCA and DA (especially issues to do with research design, data collection and transcription). Develop students understanding of methodological issues and CA/MCA/DP analytic skills. Familiarise students with current debates within the field. Further develop students ability to report, present and evaluate qualitative research. The themes covered in the module are as follows. An introduction to ethnomethodology and other historical and philosophical underpinnings. Unpacking of how CA/MCA/DP differ to other forms of qualitative research in terms of research questions, research design, data collection and transcription. 5
Data analysis techniques (description and practice with key analytic concepts). Evaluate current debates (such as context, power, and the critique of interviews as data). Testing Psychological Theories Using Structural Equation Modelling The aims of this module are to introduce you to the theoretical and philosophical underpinnings of structural equation modelling (SEM); and to equip you with the skills, and understanding, to appropriately construct, analyse, and interpret theoretical path analytic, CFA, and SEM models using LISREL software. You will also be equipped with the skills to use other advanced multivariate techniques, like latent class analysis and multinomial logistic regression. Software programmes suitable for this analysis (eg MPlus) will also be used. Students will be taken through seven sequential steps of structural equation modelling using LISREL: Model conceptualisation Path diagram construction Model specification Model identification Parameter estimation Assessment of model fit Model modification Model cross-validation Additionally the following topics will be covered: Historical, theoretical, and philosophical underpinnings of the structural equation modelling approach Alternatives to LISREL Please visit www.ntu.ac.uk/s3scholarships for fees, funding and scholarship information. Please email us at s3.enquiries@ntu.ac.uk or telephone on +44 (0)115 848 4460 for more information. 6