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Medical statistics

From Wikipedia, the free encyclopedia
Applications of statistics to medicine and the health sciences
"Statistics in Medicine" redirects here. For the journal, seeStatistics in Medicine (journal).
This articleis inlist format but may read better asprose. You can help byconverting this article, if appropriate.Editing help is available.(September 2014)

Medical statistics (alsohealth statistics) deals with applications ofstatistics tomedicine and thehealth sciences, includingepidemiology,public health,forensic medicine, andclinical research.[1] 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.[2] However, "biostatistics" more commonly connotes all applications of statistics tobiology.[2] Medical statistics is a subdiscipline 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.[3]

Use in medical hypothesis testing

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In medical hypothesis testing, the medical research is often evaluated by means of theconfidence interval, theP value, or both.[4]

Confidence interval

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Thisprobability distribution presents two differentconfidence intervals.[1]

Frequently reported in medical research studies is the confidence interval (CI), which indicates the consistency and variability of the medical results of repeated medical trials. In other words, the confidence interval shows the range of values where the expected true estimate would exist within this specific range, if the study was performed many times.[1]

Most biomedical research is not able to use a total population for a study. Instead, samples of the total population are what are often used for a study. From the sample, inferences can be made of the total population by means of a sample statistic and the estimation of error, presented as a range of values.[1][4]

P value

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Frequently used in medical studies is the statistical significance of P < 0.05.[4]

The P value is the probability of no effect or no difference (null hypothesis) of obtaining a result essentially equal to what was actually observed. The P stands for probability and measures how likely it is that any observed difference between groups is due to chance. The P value function between 0 and 1. The closer to 0, the less likely the results are due to chance. The closer to 1, the higher the probability that the results are actually due to chance.[4]

Pharmaceutical statistics

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Pharmaceutical statistics is the application of statistics to matters concerning thepharmaceutical industry. This can be from issues ofdesign of experiments, to analysis of drug trials, to issues of commercialization of a medicine.[1]

There are many professional bodies concerned with this field including:

Clinical biostatistics

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Clinical biostatistics is concerned with research into the principles and methodology used in the design and analysis ofclinical research and to applystatistical theory toclinical medicine.[1][5]

Clinical biostatistics is taught inpostgraduate biostatistical and applied statistical degrees, for example as part of theBCA Master of Biostatistics program in Australia.

Basic concepts

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For describing situations
For assessing the effectiveness of an intervention

Related statistical theory

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  • 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): 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.[6]
  • Actuarial statistics: the statistics used by actuaries to calculate liabilities, evaluate risks and plan the financial course of insurance, pensions, etc.[7]

See also

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References

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  1. ^abcdef"Finding and Using Health Statistics". US National Library of Medicine. Retrieved2024-03-15.
  2. ^abDodge, Y. (2003)The Oxford Dictionary of Statistical Terms, OUP.ISBN 0-19-850994-4
  3. ^Kirkwood, Betty R. (2003).Essential Medical Statistics. Malden, Massachusetts: Blackwell.ISBN 978-0-86542-871-3.
  4. ^abcdShreffler, Jacob; Huecker, Martin R. (2024)."Hypothesis Testing, P Values, Confidence Intervals, and Significance".StatPearls. Treasure Island (FL): StatPearls Publishing.PMID 32491353. Retrieved2024-03-16.
  5. ^"Our aims". International Society For Clinical Biostatistics. 22 February 2015. Retrieved15 March 2024.
  6. ^S, KATZ; FORD A B; MOSKOWITZ R W; JACKSON B A; JAFFE M W (1963). "Studies of Illness in the Aged".Journal of the American Medical Association.185 (12):914–9.doi:10.1001/jama.1963.03060120024016.PMID 14044222.
  7. ^Benjamin, Bernard (1993).The analysis of mortality and other actuarial statistics. England, Institute of Actuaries: Oxford.ISBN 0521077494.

Further reading

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External links

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Continuous data
Center
Dispersion
Shape
Count data
Summary tables
Dependence
Graphics
Study design
Survey methodology
Controlled experiments
Adaptive designs
Observational studies
Statistical theory
Frequentist inference
Point estimation
Interval estimation
Testing hypotheses
Parametric tests
Specific tests
Goodness of fit
Rank statistics
Bayesian inference
Correlation
Regression analysis (see alsoTemplate:Least squares and regression analysis
Linear regression
Non-standard predictors
Generalized linear model
Partition of variance
Categorical
Multivariate
Time-series
General
Specific tests
Time domain
Frequency domain
Survival
Survival function
Hazard function
Test
Biostatistics
Engineering statistics
Social statistics
Spatial statistics
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