Further Topics in Multivariate Analysis (FTMA) - Extra Run Prerequisites
This module is an extension of the three previous modules in the Basic Statistics stream, covering the theory and practice of multivariate analysis. Students will gain deeper knowledge of interaction effects in regression models and its interpretation as well as introduction to ordered and categorical regression models. You will learn why and when to use interaction between explanatory variables, to do simple marginal effects of interaction variables, to understand the principles for employing multinomial and ordered categorical models, to perform simple models or these kind, and to interpret and write about your results intelligently. Half of the module is based in the lecture theatre, and covers the theory behind interaction effects, multinomial and ordered categorical models. The other half is lab-based, in which students will work through practical exercises using Stata statistical software.
All students wishing to book a place on this module must have either:
- Completed the SSRMC Skill Check
OR
- Have successfully completed Foundations in Applied Statistics (FiAS), Basic Quantitative Analysis (BQA) and Doing Multivariate Analysis (DMA)
before a place can be booked for them.
Students that have already completed the SSRMC Skill Check may have had a place booked for them by their Department. Students can check this by typing their CRSid into the search box at the very top right of this page, hitting the enter key then clicking on their name. This will show all module(s) that they are booked onto, as applicable.
Bookings for this module can also be made via:
- The Basic Statistics Stream Booking Form on the SSRMC website.
- In cases where you have a problem or a clash, please contact the SSRMC Administrator who will try to help you.
This module is designed for MPhil and PhD students as part of the Social Science Research Methods Centre (SSRMC) training programme - a shared platform for providing research students with a broad range of quantitative and qualitative research methods skills that are relevant across the social sciences.
- Completion of Foundations in Applied Statistics (FiAS) and Basic Quantitative Analysis (BQA) and Doing Multivariate Analysis (DMA) modules (or equivalent level of knowledge, verified by the SSRMC Skill Check.
- To use the Titan Teaching Room computers you must bring your password for the Desktop Services system. Please note, your password for the Desktop Services system is distinct from your Raven/department/email password. If you are uncertain about this you are advised to go to the University Computing Service Helpdesk before the first day of class or find out more on the UCS Newcomers page.
- You must have enrolled for the module's Moodle course page
Instructions: http://www.ssrmc.group.cam.ac.uk/ssrmc-modules/moodle
Number of sessions: 4
| # | Date | Time | Venue | Trainer | |
|---|---|---|---|---|---|
| 1 | Mon 6 Feb 2017 10:00 - 12:00 | 10:00 - 12:00 | 8 Mill Lane, Lecture Room 6 | map | Dr Ricardo Sabates-Aysa |
| 2 | Mon 6 Feb 2017 16:00 - 18:00 | 16:00 - 18:00 | Phoenix Teaching Room 1, New Museums Site | map | Dr Ricardo Sabates-Aysa |
| 3 | Mon 13 Feb 2017 10:00 - 12:00 | 10:00 - 12:00 | 8 Mill Lane, Lecture Room 6 | map | Dr Ricardo Sabates-Aysa |
| 4 | Mon 13 Feb 2017 16:00 - 18:00 | 16:00 - 18:00 | Phoenix Teaching Room 1, New Museums Site | map | Dr Ricardo Sabates-Aysa |
- Introduction to the basic theory and practice of ordered logit and probit models and applications of interaction effects within regression models.
- The basic theory and practice of multinomial regression: underlying assumptions; and issues of specification, including estimation of marginal effects and interpretation.
- Learn why and when to use interaction between explanatory variables;
- Learn to do simple marginal effects of interaction variables;
- Learn to understand the principles for employing multinomial and ordered categorical models;
- Learn to perform simple models or these kind, and to interpret and write about your results intelligently.
Presentations, demonstrations and practicals
Windows
Stata on MCS
- Online test following the final session
Session 1
- Long, S. (1997) Regression models for categorical and limited dependent variables. Advanced quantitative techniques in the Social Sciences. (Recommended)
- Hayes, A. (2013). Introduction to Mediation, Moderation, and Conditional Process Analysis: A Regression-Based Approach (Methodology in the Social Sciences). Abingdon, Oxon UK: Guilford Press: (Recommended)
- Cindy D. Kam and Robert J. Franzese Jr (2007). Modelling and Interpreting Interactive Hypotheses in Regression Analysis (Optional)
Session 2
- Long, S. (1997) Regression models for categorical and limited dependent variables. Advanced quantitative techniques in the Social Sciences. (Recommended)
- Jacob Cohen, Patricia Cohen, Stephen G. West, Leona S. Aiken (2002). Applied Multiple Regression/Correlation Analysis for the Behavioral Sciences. London: Routledge. (Recommended)
All students are expected to give feedback for each module they take...
At the end of each module, students will be sent a link to a very short evaluation form. They will also be able to find this link on the Moodle page for their course. The survey takes a few minutes to fill in, and can even be done on a mobile phone. Students that do not respond to the survey the first time, will receive regular automated reminders until the survey is completed.
Students will not be given certification or proof of attendance for any module for which they have not provided feedback.
- To gain maximum benefits from the course it is important that students do not see this course in isolation from the other MPhil courses or research training they are taking.
- Responsibility lies with each student to consider the potential for their own research using methods common in fields of the social sciences that may seem remote. Ideally this task will be facilitated by integration of the SSRMC with discipline-specific courses in their departments and through reading and discussion.
4 hours (a morning lecture and an afternoon lab session) over two days.
Once a week for 2 weeks.
- Foundations in Applied Statistics (FiAS-6)
- Basic Quantitative Analysis (BQA-6)
- Doing Multivariate Analysis (DMA 3)
- Further Topics in Multivariate Analysis (FTMA) 2
Booking / availability