SeerPharma Pty Ltd :: DISCover web-based training

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Biostatistics

Description: Using real examples from the medical literature, this course will introduce you to clinical research and applied statistics. This course will prepare you to critically read and understand the medical literature.

COURSE OUTLINE

INTRODUCTION
1. Course Information
2. Interface Tour
3. Course Overview

THE RESEARCH QUESTION
4. Objectives
5. Pre-test
6. The Empirical Cycle
7. Exploratory vs. Confirmatory Studies
8. The Research Hypothesis
9. Target Population vs. Study Population
10. Progress Check

STUDY DESIGN
11. Objectives
12. Pre-test
13. Casual Inference
14. Bias and Confounding
15. Cross-sectional studies
16. Case-control studies
17. Cohort studies
18. Randomized clinical trials
19. Meta-analysis
20. Progress Check

TYPES OF MEASUREMENTS
21. Objectives
22. Pre-test
23. Variation
24. Continuous
25. Categorical
26. Time-to-event
27. Diagnostic Testing
28. Progress Check

STATISTICAL INFERENCE
29. Objectives
30. Pre-test
31. Hypothesis Testing
32. Power and Sample Size
33. Confidence Intervals
34. Multiple Comparisons
35. Progress Check

STATISTICAL ANALYSES I
36. Objectives
37. Pre-test
38. Intention to treat Analysis
39. Predictors and Outcomes

STATISTICAL ANALYSES II
40. Analysis for Continuous Outcome
41. Analysis for Categorical Outcome
42. Analysis for Time-to-event Outcome
43. Progress Check

CONCLUSION
44. Summary

COURSE OBJECTIVES

Students completing this course should be able to:

Describe the empirical cycle
Differentiate between hypothesis-generating and hypothesis-testing studies
Formulate a research hypothesis
Identify the research hypothesis in a given study
Identify the predictor and outcome in a given study
Define target population, study population, and study sample
Describe the different types of studies used in medical research
Recognize the advantages and limitations of the different study designs
Identify sources of bias in different study designs
Describe the relative strength of each type of study design in establishing causality
Describe sources of variation in medical data
Differentiate between continuous and categorical data
Define time-to-event data
Define mean and standard deviation
Identify how data were measured in real studies
Describe how diagnostic tests are evaluated
Define and calculate sensitivity, specificity, negative predictive value, and positive predictive value
Describe sampling variation
Formulate a null hypothesis
Interpret a p-value
Define type I and type II errors
Differentiate between statistical and clinical significance
Understand statistical power
Interpret a confidence interval
Describe the problem of multiple comparisons
Describe the intention-to-treat principle
Explain last observation carried forward
Calculate odds ratios and risk ratios
Interpret odds ratios, risk ratios, and hazard ratios
Understand the results of simple statistical tests
Recognize the names of more advanced statistical tests
Identify the appropriate statistical test for a given study design and type of data
Understand common pitfalls in medical statistics
Current bioinformatics tools and databases

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SeerPharma has partnered with GeneEd to now distribute courses in Major Therapeutic Areas, Clinical Research, and Biotechnology & Genetics.