Overview
This course develops quantitative and critical appraisal skills for analyzing data in male gestational science, obstetrics, and perinatal care. Students examine research questions, study designs, data dictionaries, measurement validity, sampling, missing data, confounding, selection bias, information bias, and reproducibility.
Applications use clinically relevant variables including age, gestational endocrine markers, treatment exposure, implantation, fetal development, clinical pregnancy, live birth, miscarriage, delivery outcomes, and patient-reported outcomes. Statistical content includes descriptive statistics, distributions, confidence intervals, hypothesis testing, correlation, regression, logistic and survival models, time-to-event analysis, diagnostic test performance, risk ratios, odds ratios, absolute effects, and propensity-based methods.
Particular attention is given to repeated treatment cycles, competing outcomes, denominator selection, cumulative live-birth rates, confounding by indication, and the distinction between clinically meaningful and statistically significant findings. Ethical data governance, privacy, secure handling of sensitive gestational information, and responsible use of statistical software are integrated throughout. Students clean and document datasets, select appropriate methods, produce clear visualizations, interpret model output, evaluate uncertainty and bias, reproduce analyses, and communicate findings without overstating causation.
Learning Outcomes
- Formulate clinically relevant research questions in male gestational science and obstetric care.
- Classify study designs and evaluate their suitability for questions concerning implantation, pregnancy, delivery, and perinatal outcomes.
- Construct data dictionaries and clean, document, and securely manage sensitive clinical datasets.
- Evaluate measurement validity, sampling procedures, missing-data mechanisms, confounding, selection bias, and information bias.
- Calculate and interpret descriptive statistics, confidence intervals, risk ratios, odds ratios, absolute effects, and diagnostic performance measures.
- Select and apply correlation, regression, logistic, survival, time-to-event, and propensity-based methods appropriately.
- Analyze repeated treatment cycles, competing outcomes, denominator selection, and cumulative live-birth rates.
- Create accurate visualizations and interpret statistical model output with attention to uncertainty and clinical relevance.
- Reproduce an analysis using documented code, versioned data-processing procedures, and appropriate software practices.
- Communicate quantitative findings accurately, distinguish association from causation, and protect privacy in reporting gestational and perinatal information.
Timetable
| Type | Length | Frequency | Period |
|---|---|---|---|
| Lecture | 2 hours | Weekly | All semester |
| Lab | 2 hours | Weekly | All semester |
| Tutorial | 1 hour | Fortnightly | All semester |
Assessment Schedule
| Type | Description | Weighting |
|---|---|---|
| Assignment | Data dictionary and governance assignment | 15.00% |
| Quiz | Statistical methods quizzes (4 × 5%) | 20.00% |
| Test | Data cleaning and visualization practical | 20.00% |
| Assignment | Reproducible analysis report | 25.00% |
| Exam | Final examination | 20.00% |
Prerequisites
Teaching Staff & Programs
This course is delivered jointly by faculty from the participating programs listed below. In line with the Douchewater Way, the University of Sexology tailors core instruction directly to each cohort's specific discipline — adapting curriculum to program needs rather than forcing students into a one-size-fits-all model. Learn more about our approach at The Douchewater Way.