Advanced Statistics and Research Methods
Full course description
The module ‘Advanced statistics and research methods’ extends the statistical data-analytic tools, as treated in GZW1026 (“Introduction to statistical methods for data-analysis”), and broadens and elaborates on methodological issues in research in health sciences, as treated in GZW1023 (“Introduction to scientific research methods”). Central are four methodological-statistical themes, which will be treated from a multidisciplinary perspective, integrating both statistical and methodological issues:
(I) Quantitative research into and evaluation of causal relations between determinants and health related outcomes, with two subthemes:(A) observational research, and (B) experimental research;
(II) Research into the quality of measurements and measurement devices;
(III) Planning quantitative research;
(IV) Critical reading of and assessing the quality of scientific articles, based on the methods and statistics section.
The latter theme fits in the curriculum critical reading as part of the trajectory academic development. Each theme will be illustrated by real-life examples, where possible problems and dilemmas from the practice of health science research are discussed. Also the relation between methodological and statistical aspects of scientific research are addressed. These aspects are elaborated through different educational formats (lectures, seminars, skills trainings, assignments). Two themes (I and II) will close with a seminar in which a real-life problem of the theme is addressed and in which methodological and statistical aspects are discussed in an integrated way.
Course objectives
After completing the course the student will have knowledge of and insight into:
- Important experimental and observational research designs;
- Selection bias, information bias and confounding;
- Effect-modification and interaction;
- Multiple linear, logistic and linear marginal model regression as instruments for research into causality;
- Relation between linear regression and AN(C)OVA;
- Different forms of and statistical techniques for examining reliability, validity and agreement;
- Power of a test and techniques to determine the required sample size;
- Different forms of selection strategies and methods to interpret results of systematic literature research;
- Relation between a health sciences research question, number and measurement levels of variables on the one hand, and choice of a research design and statistical technique on the other.
After completing the course the student can:
- Calculate and interpret measures of association for different research designs;
- Perform linear, logistic and linear marginal model regression in SPSS;
- Perform a stratified and multivariate analysis to examine confounding and effect-modification;
- Apply techniques to examine reliability, validity and agreement, within SPSS;
- Assess the quality of diagnostic and screening tests;
- Perform simple sample size calculations with Gpower;
- Make a motivated choice from research designs and statistical analysis techniques;
- Adequately interpret research results from a methodological and statistical perspective;
- Evaluate the causality of a relation between determinants and health related outcomes.
- Accurately report the results of statistical analyses (written and verbally);
- Can pursue education in statistics and methodology.
Recommended reading
Basic literature: Berger, M.P.F., Imbos, Tj. & Janssen, M.P.E. (2008). Methodologie en Statistiek 2. (Vol. 2). Maastricht: Universitaire Pers Maastricht. Bouter, L.M., van Dongen, M.C.J.M., Zielhuis, G.A., Zeegers M. (2015). Leerboek epidemiologie: Opzet en interpretatie. Houten: Bohn Stafleu Van Loghum. Field, A. (2018). Discovering statistics using IBM SPSS statistics, 5th edition, London: Sage. Fletcher, Fletcher & Fletcher (2014). Clinical Epidemiology: The Essentials. Fifth Edition, Baltimore: Wolters Kluwer / Lippincott Williams & Wilkins. Additional literature as referred to in the seminars