Statistical Symbols and Abbreviations - Study Design and Statistics

AMA Manual of Style - Stacy L. Christiansen, Cheryl Iverson 2020

Statistical Symbols and Abbreviations
Study Design and Statistics

The following may be used without expansion except where noted. For a term expanded at first mention, the abbreviation may be placed in parentheses after the expanded term and the abbreviation used thereafter (see 13.11, Clinical, Technical, and Other Common Terms). Most terms other than mathematical symbols can also be found in 19.5, Glossary of Statistical Terms.

Symbol or abbreviation

Description

|x|

absolute value

sum

>

greater than

greater than or equal to

<

less than

less than or equal to

^

hat, used above a parameter to denote an estimate

ANOVA

analysis of variance (expand at first mention)

ANCOVA

analysis of covariance (expand at first mention)

AR

autoregression

α

alpha, probability of type I error

1 − α

confidence coefficient

β

beta, probability of type II error or population regression coefficient

1 − β

power of a statistical test

b

sample regression coefficient

CI

confidence interval

C statistic

concordance statistic (same as C index)

Image (chi-square)

χ2 test or statistic, with 3 df shown as an example

CV

coefficient of variation (s/x̄) × 100 (expand at first mention)

d

Cohen d

D

difference

df

degrees of freedom (v is the international symbol149 and also may be used if familiar to readers)

D2

Mahalanobis distance, distance between the means of 2 groups

Δ

delta, change, difference

δ

delta, true sampling error

epsilon, true experimental error

e

exponential

E(x)

expected value of the variable x

f

frequency or a function of, usually followed by an expression in parentheses, eg, f(x)

F

F test, ratio of 2 variances. This test can be represented by Fv1,v2(1 − α), where df = v1, v2 for numerator and denominator, respectively, and (1 − α) = confidence coefficient

G2(df)

likelihood ratio χ2

HR

hazard ratio (expand at first mention)

H0

null hypothesis

H1

alternate hypothesis; specify whether 1- or 2-sided

I2

test for heterogeneity

κ

kappa statistic

λi

lambda, hazard function for interval i; eigenvalue; or estimate of parameter for log-linear models

Λ

Wilks lambda

ln

natural logarithm

log

logarithm to base 10 (log10)

MANOVA

multivariate analysis of variance (expand at first mention)

μ

population mean

n

size of a subsample

N

total sample size

n!

(n) factorial

OR

odds ratio (expand at first mention)

P

statistical probability

r

bivariable coefficient of determination

R

multivariable correlation coefficient

r 2

bivariable coefficient of determination

R 2

multivariable coefficient of determination

RR

relative risk (expand at first mention)

ρ

rho, population correlation coefficient

s2

sample variance

σ2

sigma squared, population variance

σ

sigma, population SD

SD

standard deviation of a sample, can also mean standardized difference

SE

standard error

SEM

standard error of the mean

t

t test; specify α level, df, 1-tailed vs 2-tailed

τ

Kendall tau

T2

Hotelling T2 statistic

u

Mann-Whitney U (Wilcoxon) statistic

Image

arithmetic mean

z

z score

Principal Author: Edward H. Livingston, MD

Acknowledgment

Thanks to the following for reviewing and providing comments to improve the manuscript: Miriam Cintron, JAMA; Trevor Lane, MA, DPhil, Edanz Group, Fukuoka, Japan; Tom Lang, MA, Tom Lang Communications, Kirkland, Washington; and Ana Marušić, MD, PhD, Journal of Global Health and University of Split School of Medicine, Croatia.

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Additional Reading and General References

Elliott AC, Woodward WA. Statistical Analysis Quick Reference Guidebook: With SPSS Examples. Sage Publications; 2007.

Guyatt G, Rennie D, Meade M, Cook D, American Medical Association. Users’ Guides to the Medical Literature: A Manual for Evidence-Based Clinical Practice. 3rd ed. McGraw-Hill Education Medical; 2015.

Livingston EH, Lewis RJ. JAMA Guide to Statistics and methods. McGraw-Hill Education; 2020.

JAMAevidence. Accessed November 9, 2019. https://jamaevidence.mhmedical.com

Motulsky H. Intuitive Biostatistics: A Nonmathematical Guide to Statistical Thinking. 3rd ed. Oxford University Press; 2014.

Riegelman RK, Riegelman RK. Studying a Study & Testing a Test: Reading Evidence-Based Health Research. 6th ed. Wolters Kluwer/Lippincott Williams & Wilkins Heath; 2013.

Rothman KJ, Greenland S, Lash TL. Modern Epidemiology. 3rd ed. Wolters Kluwer Health/Lippincott Williams & Wilkins; 2008.