How to use (3 steps)
- Select an example or paste standards (concentration and signal).
- Choose 4PL/5PL, weighting, and other settings.
- The curve and unknown concentrations appear (extrapolation is flagged).
This is a model. Extrapolation outside the standard range can be inaccurate. Use blank subtraction only when needed.
Inputs (standards, unknowns, settings)
—
Display options
Minimum columns: concentration and signal. Multiple rows with the same concentration are treated as replicates.
Minimum columns: sample and signal. If dilution_factor is blank, it is treated as 1.
Results (curve & concentrations)
R² and AIC are guides. Also check residuals and whether values are extrapolated.
Standard curve
Residual plot (optional)
Parameters (A, B, C, D, G)
| param | value | 95% CI (approx) |
|---|
Guide: A=Bottom (low concentration), D=Top (high), C=EC50 (midpoint), B=Hill slope, G=asymmetry (5PL only). Internally we compute (x/C)^B as exp(B·ln(x/C)). Log10 on x-axis is for readability.
QC (back-calculation / recovery)
| label | conc_nominal | signal_mean | conc_hat | recovery |
|---|
Unknowns (y → concentration)
| sample | signal_mean | DF | conc_measured | conc_original | flag |
|---|
How it’s calculated
- Fit a 4PL/5PL logistic curve with nonlinear least squares.
- Unknown concentrations are computed by inverting the fitted curve.
- Weighting (1/y, 1/y², etc.) can help handle variance across concentration ranges.
Values are guides. Also check outliers, standard ranges, and dilution conditions.
How to use this calculator effectively
This guide helps you use ELISA standard curve fitter (4PL/5PL) in a repeatable way: set a baseline, change one variable at a time, and interpret the output with clear assumptions before sharing or exporting results.
How it works
The calculator takes your input values, applies a deterministic formula set, and returns output using display rounding only at the final step. This means the tool is best used as a comparison engine: keep one scenario as a reference, then test alternate assumptions so you can quantify how sensitive the final answer is to each input.
When to use
Use this page when you need a fast planning estimate, a classroom sanity check, or a shareable scenario that another person can reproduce from the same parameters. It is especially useful before deeper modeling, because it exposes direction and magnitude quickly without requiring sign-in or setup friction.
Common mistakes to avoid
- Mixing units (for example, percent vs decimal, or monthly vs yearly assumptions).
- Changing multiple fields at once, which makes it hard to explain why results shifted.
- Comparing outputs from different tools without aligning defaults and conventions.
- Reading rounded display numbers as exact values in downstream calculations.
Interpretation and worked example
Run a baseline case first and keep a copy of that output. Next, change one assumption to represent your realistic alternative, then compare the delta in both absolute and percentage terms. If the direction matches your domain intuition and the size of change is plausible, your setup is likely coherent. If not, review units, sign conventions, and hidden defaults before drawing conclusions.
See also
How to use this calculator effectively
This calculator is designed to make scenario checks fast. Use a repeatable workflow: baseline first, one variable change at a time, then compare output direction and magnitude.
How it works
Run your first scenario with defaults. Then, change exactly one assumption and observe which result changes most. That is the fastest way to identify sensitivity and explain what drives the outcome.
When to use
Use this page when you need practical planning support, side-by-side alternatives, or a clean baseline for further discussion.
Common mistakes to avoid
- Changing multiple assumptions simultaneously.
- Confusing percent and decimal inputs.
- Mixing unit systems across scenarios.
- Relying only on rounded display output for final conclusions.
Worked example
Prepare a base case and one alternative case, then compare outputs and validate the direction, scale, and interpretation with the same assumptions across both cases.
See also
FAQ
Should I use 4PL or 5PL?
4PL is often sufficient. Use 5PL if asymmetry is needed (compare with AIC, etc.).
Do I need weighting (1/y, 1/y²)?
Not required. Start without weighting and try it if bias appears across the range.
How should I handle concentration 0 (blank)?
By default, blanks are excluded from fitting (works well with log x). Use blank subtraction only if needed.
An unknown value is outside the standard range.
It will be shown as extrapolated. Accuracy drops, so dilute and remeasure within range.
What should I enter first?
Start with the minimum required inputs shown above the calculate button, then keep optional settings at their defaults for a first run. After you get a baseline result, change one parameter at a time so you can see exactly what caused the output to move.
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