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BMES-862 Clinical Biostatistics
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Campus
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SMME
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Programs
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PG
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Session
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Fall Semester 2016
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Course Title
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Clinical Biostatistics
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Course Code
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BMES-862
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Credit Hours
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3
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Pre-Requisutes
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None
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Course Objectives
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- To learn the principles of the statistical methods described, particularly their appropriate use and their limitations.
- To read papers of the type published in the Medical Journals, understanding the statistical methods employed, their rationale and interpretation, and comment on their appropriateness.
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Detail Content
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- Decommentive statistics: Type of data, frequency, distribution, histograms and other frequency graphs, symmetry and skewness, median and other quantiles, mean, range, inter-quantile ranges, variance, standard deviation. Estimation, standard error and confidence intervals Normal distribution, sampling variation and sampling distributions, standard error, confidence intervals.
- Significance tests: Sign test as an example, principles of significance tests, hypotheses, types of error, presenting P values, multiple testing, one- and two-sided tests.
- Comparing means: Large sample Normal methods, two sample t method, checking assumptions, Normal plot, deviations from assumptions, Satterthwaite correction, paired t methods, checking assumptions, deviations from assumptions, analysis of variance, checking assumptions, deviations from assumptions, comparison of means after anova.
- Transformations: Need for transformations, frequently used transformation, logarithms, logarithmic scales, interpreting transformed data in a single sample, choosing transformation when comparing samples and interpreting transformed data, transformations for paired data, data which cannot be transformed, are transformations a valid approach?
- Categorical data: Chi-squared and Fisher’s tests, Yates’ correction, chi-squared test for trend, relative risk, odds ratios, number needed to treat.
- Correlation and regression: Correlation coefficients, regression lines, multiple regression, categorical predictors, regression and t tests, use of regression in clinical trials, logistic regression, interactions, minimum samples sizes for regression.
- Survival data: Time to event data and censoring, Kaplan Meier estimates and survival curves, logrank test, Cox regression, checking assumptions.
- Sampling Theory: Basic concepts: The importance and practical use of sample surveys; comparison of sample and census. Simple random sampling: estimation of a population mean and proportion; choice of sample size. Stratified random sampling: estimation, criteria for good stratification, allocation of sample strata sizes, when to stratify. Other sampling methods: Questionnaire design and survey methods, preparation and organization of a survey.
- Design of Experiments: Notation: Design region. Variation and blocking. Stages in experimental research. Randomisation. Criteria for a good experiment: Optimality criteria. General theory of block designs. Factorial designs: Estimability. Blocking. Confounding. Screening. Response surface designs Optimum Design theory: General Equivalence Theorem. Experiments with constraints. Design construction.
Course Outcomes
- At the end of the course the students should understand the principles of the statistical methods described, particularly their appropriate use and their limitations. Students should be able to read papers of the type published in the Medical Journals, understanding the statistical methods employed, their rationale and interpretation, and comment on their appropriateness.
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Text/Ref Books
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- Bland M. An introduction to medical statistics. Oxford University Press, 2000
- Altman DG. Practical statistics for medical research. London: Chapman and Hall,
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Time Schedule
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Faculty/Resource Person
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Asst Prof Dr Zaib Ali
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