What this calculator works out
This calculator applies a linear regression equation — a coefficient, an intercept and a standard error — to a long bone measurement, giving an estimated living stature with a range either side.
The equation is not built in. You supply it, and the equation you choose determines the answer. Using one derived from a different population, sex or bone produces an estimate that can be several centimetres wrong. This is a teaching aid, not a casework tool.
Regression equation
Stature = coefficient × bone length + intercept
Before you calculate
- Select an equation appropriate to the population, sex and specific bone. Trotter and Gleser's equations remain widely used and are published separately for each combination.
- Measure the bone using the standard definition for that equation — maximum length on an osteometric board, following the convention the original study used.
- The default values are the Trotter and Gleser femur equation for one specific population and sex. They are an illustration, not a default to accept.
- Report the standard error. An estimate without it implies a precision the method does not have.
Trotter's tibia equations are known to have been derived using a measurement that excluded the intercondylar eminence, which was not clearly stated at the time. Applying them to a maximum tibial length measured the usual way produces a systematic overestimate of around 2 to 3 cm. It is a well-documented example of why the measurement convention matters as much as the equation.
How this calculator works
A linear equation with a stated error:
Estimated stature = (coefficient × bone length) + intercept
Range = estimate ± standard errorThe standard error is a property of the original regression — it describes the scatter of individuals around the fitted line in the reference sample. Roughly two thirds of individuals fall within one standard error and about 95% within two.
Stature also declines with age, and forensic estimates are of maximum adult stature rather than stature at death. Reported living heights are frequently self-reported and unreliable, which complicates comparison.
Worked example: a 46 cm femur
Using the default figures — a 46 cm bone, coefficient 2.32, intercept 65.53, standard error 3.94:
- Estimate: (2.32 × 46) + 65.53 = 172.25 cm
- Range: 168.31 to 176.19 cm
That range is nearly 8 cm wide at one standard error, and about 16 cm at two. Anyone expecting stature estimation to narrow a search to a few centimetres is expecting the wrong thing from it. Apply an equation for a different population — coefficients for the same bone vary by roughly 2.3 to 2.9 — and the point estimate moves by several centimetres on top of that.
Common mistakes
- Using an equation from the wrong population or sex. The largest and most avoidable source of error.
- Measuring the bone by a different convention than the equation assumed.
- Omitting the standard error. The range is part of the result.
- Accepting the defaults. They illustrate one equation for one population and sex.
- Comparing against a self-reported height. Those are frequently inaccurate.
Frequently asked questions
Which bone gives the best estimate?
The femur generally has the strongest correlation with stature and the smallest standard error, followed by the tibia. Upper limb bones correlate less well. Where several bones are available, estimates from each can be compared, and agreement between them is more informative than any single figure.
How is sex determined before choosing an equation?
Primarily from the pelvis, which is the most reliable skeletal indicator, supported by cranial features and by metric analysis of joint dimensions. Where sex cannot be determined, some analysts apply both equations and report the combined range, which is wider but honest.
Why are the equations population-specific?
Because limb proportions differ between populations, so the relationship between a given bone length and total stature is not universal. Applying an equation derived from one reference sample to an individual from a different background introduces systematic error that the standard error does not capture.
What if only a fragment survives?
Regression equations exist for estimating complete bone length from measured fragments, and that estimate then feeds into a stature equation. Each step adds error, so the final range widens substantially. The Long Bone Percentage Calculator gives a sense of how much of a bone is present before that chain begins.
Is what I enter stored?
No. Measurements are processed entirely in your browser and never transmitted or retained. Do not enter identifiable case information into any public website.
Related tools
References
- GOV.UK — Forensic Science Regulator codes of practice for anthropological analysis
- National Institute for Health and Care Excellence — clinical guidance on measurement and reference ranges
Sources are checked at publication and can change — how I choose and check references.