Basics of Biostatistics

Descriptive statistics
Continuous data
Location
•Mean (Arithmetic, Geometric, Harmonic) · Median · Mode
Dispersion
•Range · Standard deviation · Coefficient of variation · Percentile
Moments
•Variance · Semivariance · Skewness · Kurtosis

Categorical data
•Frequency · Contingency table


Inferential statistics and hypothesis testing
Inference
•Confidence interval (Frequentist inference) · Credible interval (Bayesian inference)· Significance· Meta-analysis

Design of experiments
•Population · Sampling· Stratified sampling · Replication · Blocking · Sensitivity and specificity

Sample size estimation
•Statistical power· Effect size · Standard error

General estimation
•Bayesian estimator · Maximum likelihood · Method of moments · Minimum distance · Maximum spacing

Specific tests
•Z-test (normal) · Student's t-test · F-test · Chi-square test · Pearson's chi-square test · Wald test· Mann–Whitney U · Wilcoxon signed-rank test

Survival analysis
•Survival function · Kaplan-Meier · Logrank test · Failure rate · Proportional hazards models


Correlation and regression
Correlation
•Pearson product-moment correlation · Rank correlation (Spearman's rho, Kendall's tau) · Confounding variable

Linear models
•General linear model · Generalized linear model · Analysis of variance · Analysis of covariance

Regression analysis
•Linear · Nonlinear · Nonparametric · Semiparametric · Logistic

For proper planning of a scientifically sound study a strong biostatistical basis is most essential

Evidence Based Medicine

According to the Centre for Evidence-Based Medicine, "Evidence-based medicine is the conscientious, explicit and judicious use of current best evidence in making decisions about the care of individual patients


Evidence-based medicine attempts to objectively evaluate the quality of clinical research by critically assessing techniques reported by researchers in their publications.
•Trial design considerations. High-quality studies have clearly-defined eligibility criteria, and have minimal missing data.
•Generalizability considerations. Studies may only be applicable to narrowly-defined patient populations, and may not be generalizable to clinical practice.
•Followup. Sufficient time for defined outcomes to occur can influence the study outcomes and the statistical power of a study to detect differences between a treatment and control arm.
•Power. A mathematical calculation can determine if the number of patients is sufficient to detect a difference between treatment arms. A negative study may reflect a lack of benefit, or simply a lack of sufficient quantities of patients to detect a difference.

Types of Clinical Research Studies

Treatment studies

•Randomized controlled trial
–Double-blind randomized trial
–Single-blind randomized trial
–Non-blind trial

•Nonrandomized trial (quasi-experiment)
–Interrupted time series design (measures on a sample or a series of samples from the same population are obtained several times before and after a manipulated event or a naturally occurring event) - considered a type of quasi-experiment

Observational studies
•Cohort study
–Prospective cohort
–Retrospective cohort
–Time series study

•Case-control study
–Nested case-control study

•Cross-sectional study
–Community survey

Presently for orthopedic literature the following heirarchy of evidence is followed in most peer reviwed journals