Medical statistics

Medical statistics deals with applications of statistics to medicine and the health sciences, including epidemiology, public health, forensic medicine, and clinical research. Medical statistics has been a recognized branch of statistics in the United Kingdom for more than 40 years but the term has not come into general use in North America, where the wider term 'biostatistics' is more commonly used.^[1] However, "biostatistics" more commonly connotes all applications of statistics to biology.^[1] Medical Statistics are a sub discipline of Statistics. "It is the science of summarizing, collecting, presenting and interpreting data in medical practice, and using them to estimate the magnitude of associations and test hypotheses. It has a central role in medical investigations. It not only provides a way of organizing information on a wider and more formal basis than relying on the exchange of anecdotes and personal experience, but also takes into account the intrinsic variation inherent in most biological processes." ^[2]

Pharmaceutical statistics

Pharmaceutical statistics is the application of statistics to matters concerning the pharmaceutical industry. This can be from issues of design of experiments, to analysis of drug trials, to issues of commercialization of a medicine.

There are many professional bodies concerned with this field including:

European Federation of Statisticians in the Pharmaceutical Industry (EFSPI)
Statisticians In The Pharmaceutical Industry (PSI)

There are also journals including:

Basic concepts

For describing situations

Incidence (epidemiology) vs. Prevalence vs. Cumulative incidence
all types of medical test results can be true positive or false positive and true negative or false negative...these categories are hugely dependent on the prevalence of the disease being tested for; and, for example, a false positive test result is more likely when the prevalence of the disease being tested for is very low (such as a lab test for cold-weather influenza being done in June in South Carolina, USA. and giving a "positive" result).
Transmission rate vs. Force of infection
Mortality rate vs. Standardized mortality ratio vs. Age-standardized mortality rate
Pandemic vs. Epidemic vs. Endemic vs. Syndemic
Serial interval vs. Incubation period
Cancer cluster
Sexual network
Years of potential life lost
Maternal mortality rate
Perinatal mortality rate
Low Birth weight ratio

For assessing the effectiveness of an intervention

Related statistical theory

Survival analysis
Proportional hazards models
Active control trials: Clinical trials in which a kind of new treatment is compared with some other active agent rather than a placebo.
ADLS(Activities of daily living scale): It is a scale designed to measure physical ability/disability that is used in investigations of a variety of chronic disabling conditions, such as arthritis. This scale is based on scoring responses to questions about self-care, grooming, etc.^[3]
Actuarial statistics: The statistics used by actuaries to calculate liabilities, evaluate risks and plan the financial course of insurance, pensions, etc.^[4]

References

1 2 Dodge, Y. (2003) The Oxford Dictionary of Statistical Terms, OUP. ISBN 0-19-850994-4
↑ Kirkwood, Betty R. (2003). essential medical statistics. Blackwell Science, Inc., 350 Main Street, Malden, Massachusetts 02148–5020, USA: Blackwell. ISBN 978-0-86542-871-3.
↑ S, KATZ; FORD A B; MOSKOWITZ R W; JACKSON B A; JAFFE M W (1963). "STUDIES OF ILLNESS IN THE AGED. THE INDEX OF ADL: A STANDARDIZED MEASURE OF BIOLOGICAL AND PSYCHOSOCIAL FUNCTION". Journal of the American Medical Association. 185: 914. doi:10.1001/jama.1963.03060120024016.
↑ Benjamin, Bernard (1993). The analysis of mortality and other actuarial statistics. England, Institute of Actuaries,: Oxford. ISBN 0521077494.

External links

Health-EU Portal EU health statistics

Statistics

Descriptive statistics

Continuous data

Center	Mean arithmetic geometric harmonic Median Mode
Dispersion	Variance Standard deviation Coefficient of variation Percentile Range Interquartile range
Shape	Moments Skewness Kurtosis L-moments

Count data

Index of dispersion

Summary tables

Dependence

Graphics

Data collection

Study design	Population Statistic Effect size Statistical power Sample size determination Missing data
Survey methodology	Sampling stratified cluster Standard error Opinion poll Questionnaire
Controlled experiments	Design control optimal Controlled trial Randomized Random assignment Replication Blocking Interaction Factorial experiment
Uncontrolled studies	Observational study Natural experiment Quasi-experiment

Statistical inference

Statistical theory

Frequentist inference

Point estimation	Estimating equations Maximum likelihood Method of moments M-estimator Minimum distance Unbiased estimators Mean-unbiased minimum-variance Rao–Blackwellization Lehmann–Scheffé theorem Median unbiased Plug-in
Interval estimation	Confidence interval Pivot Likelihood interval Prediction interval Tolerance interval Resampling Bootstrap Jackknife
Testing hypotheses	1- & 2-tails Power Uniformly most powerful test Permutation test Randomization test Multiple comparisons
Parametric tests	Likelihood-ratio Wald Score

Specific tests

Z (normal) Student's t-test F
Goodness of fit	Chi-squared Kolmogorov–Smirnov Anderson–Darling Lilliefors Jarque–Bera Normality (Shapiro–Wilk) Likelihood-ratio test Model selection Cross validation AIC BIC
Rank statistics	Sign Sample median Signed rank (Wilcoxon) Hodges–Lehmann estimator Rank sum (Mann–Whitney) Nonparametric anova 1-way (Kruskal–Wallis) 2-way (Friedman) Ordered alternative (Jonckheere–Terpstra)

Bayesian inference

Correlation	Pearson product-moment Partial correlation Confounding variable Coefficient of determination
Regression analysis	Errors and residuals Regression model validation Mixed effects models Simultaneous equations models Multivariate adaptive regression splines (MARS)
Linear regression	Simple linear regression Ordinary least squares General linear model Bayesian regression
Non-standard predictors	Nonlinear regression Nonparametric Semiparametric Isotonic Robust Heteroscedasticity Homoscedasticity
Generalized linear model	Exponential families Logistic (Bernoulli) / Binomial / Poisson regressions
Partition of variance	Analysis of variance (ANOVA, anova) Analysis of covariance Multivariate ANOVA Degrees of freedom

Categorical / Multivariate / Time-series / Survival analysis

Categorical

Multivariate

Time-series

General	Decomposition Trend Stationarity Seasonal adjustment Exponential smoothing Cointegration Structural break Granger causality
Specific tests	Dickey–Fuller Johansen Q-statistic (Ljung–Box) Durbin–Watson Breusch–Godfrey
Time domain	Autocorrelation (ACF) partial (PACF) Cross-correlation (XCF) ARMA model ARIMA model (Box–Jenkins) Autoregressive conditional heteroskedasticity (ARCH) Vector autoregression (VAR)
Frequency domain	Spectral density estimation Fourier analysis Wavelet

Survival

Survival function	Kaplan–Meier estimator (product limit) Proportional hazards models Accelerated failure time (AFT) model First hitting time
Hazard function	Nelson–Aalen estimator
Test	Log-rank test

Applications

Biostatistics	Bioinformatics Clinical trials / studies Epidemiology Medical statistics
Engineering statistics	Chemometrics Methods engineering Probabilistic design Process / quality control Reliability System identification
Social statistics	Actuarial science Census Crime statistics Demography Econometrics National accounts Official statistics Population statistics Psychometrics
Spatial statistics	Cartography Environmental statistics Geographic information system Geostatistics Kriging

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