Module Title: | Advanced Data Analysis and Modelling |
Language of Instruction: | English |
Module Aim: |
To introduce the students to a wide variety of Data-Analysis, Statistical and Modelling Techniques. (The emphasis will be on description and usefulness of the techniques studied rather than with routine calculations).
To analyse a number of practical problems using computer facilities. Understanding issues to consider when designing a trial. Understanding the key statistical components involved in the planning and conduct of clinical trials.
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Learning Outcomes |
On successful completion of this module the learner should be able to: |
LO1 |
Describe the key elements for the importance of good experimental design and apply the appropriate data-analytic techniques. |
LO2 |
Describe and discuss key issues to consider when designing a clinical trial and the key statistical components involved in the planning and conduct of clinical trials. |
LO3 |
Apply and recognise practical situations where a statistical or a deterministic model is appropriate. |
Pre-requisite learning |
Module Recommendations
This is prior learning (or a practical skill) that is recommended before enrolment in this module.
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No recommendations listed |
Incompatible Modules
These are modules which have learning outcomes that are too similar to the learning outcomes of this module. |
No incompatible modules listed |
Co-requisite Modules
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No Co-requisite modules listed |
Requirements
This is prior learning (or a practical skill) that is mandatory before enrolment in this module is allowed. |
No requirements listed |
Module Content & Assessment
Indicative Content |
Data managment
Priciples of good data managment. Key elements of a good graph and data visualisation. Review of types of data, confidence intervals and P values. Understanding and interpreting treatment effects, statistical significance, effect size, The principle of parsimony.
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Statistical tests
Parametric vs nonparametric tests. Review of key statistical tests: Tests for differences in means. Student’s T-Test, Analysis-of-Variance (ANOVA). Correlations and Significance of regression. Linear, Polynomial and Multiple Regression.
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Experimental Design
Fundamental Principles of Good Design. Awareness of different types of outcomes and be able to select the appropriate statistical technique for the type of outcome and study design.
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Biostatistics
Bioassays, bioavailability and bioequivalence. Prevalence and incidence. Study designs: cross-sectional, cohort, case-control, experimental, randomised control trials. Efficacy, dose response relationship, placebos. Understanding different types of trial designs and be able to choose the relevant design for a given question.
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Clinical Trials
The role of the statistics in drug development. Understanding the key statistical components involved in the planning and conduct of clinical trials. Design configurations and issues, Parallel Group Design, Crossover Design, Factorial Designs. Design Techniques to Avoid Bias, Blinding, Randomization. Control groups, confounding factors. Statistical versus clinical significance. Study protocol.
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Deterministic models and pharmacokinetics
The application of differential equations including pharmacokinetics such as variation of drug and metabolic levels in various fluids and tissues of the body, compartment models for mixtures, rates of drug absorption and elimination, elimination half-life and dose determination for anesthetic drugs.
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Assessment Breakdown | % |
Continuous Assessment | 30.00% |
Practical | 30.00% |
End of Module Formal Examination | 40.00% |
Special Regulation |
Students must achieve a minimum grade (35%) in both the practical/CA and final examination. |
Continuous Assessment |
Assessment Type |
Assessment Description |
Outcome addressed |
% of total |
Assessment Date |
Practical/Skills Evaluation |
Typically may include assignments, quizzes, analysis of data sets or examination. |
1,2,3 |
30.00 |
n/a |
Practical |
Assessment Type |
Assessment Description |
Outcome addressed |
% of total |
Assessment Date |
Practical/Skills Evaluation |
Practical exam and assignments |
1,2,3 |
30.00 |
n/a |
End of Module Formal Examination |
Assessment Type |
Assessment Description |
Outcome addressed |
% of total |
Assessment Date |
Formal Exam |
Exam questions |
1,2,3 |
40.00 |
End-of-Semester |
SETU Carlow Campus reserves the right to alter the nature and timings of assessment
Module Workload
Workload: Full Time |
Workload Type |
Frequency |
Average Weekly Learner Workload |
Lecture |
12 Weeks per Stage |
2.00 |
Practicals |
12 Weeks per Stage |
2.00 |
Independent Learning Time |
15 Weeks per Stage |
5.13 |
Total Hours |
125.00 |
Module Delivered In
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