Bayes calculator for a diagnostic test
Bayes calculator for a diagnostic test - positive and negative predictive value, likelihood ratios and a confusion matrix from prevalence, sensitivity and specificity
Answeringour last check, 2026-10-20
1 of 1checks answered this week
281 msmedian answer time
$0.01listed price per call
$0.01price it asked us
Paid test badge: not yet. The checks above are free: we call the tool without paying and read the payment request it sends back. The Verified badge needs paid calls whose answers match the promised output, and nobody can buy a badge.
Endpoint
GET https://saylorinnovations.com/api/stats/bayes
| Category | Everything else |
|---|---|
| Provider host | saylorinnovations.com |
| Networks | eip155:137, eip155:42161, eip155:8453, solana:5eykt4UsFv8P8NJdTREpY1vzqKqZKvdp |
| Payment schemes | exact |
| Self-reported calls, 30 days | 0 from 0 payers (the provider's figure, not ours) |
Our checks, last 30 days
| Day | Result | HTTP | Asked | Time |
|---|---|---|---|---|
| 2026-10-20 | valid payment request | 402 | $0.01 | 281 ms |
Example input (from the provider)
{
"method": "GET",
"queryParams": {
"prevalence_percent": "1",
"sensitivity_percent": "95",
"specificity_percent": "90"
},
"type": "http"
}
Promised output schema (from the provider)
{
"$schema": "https://json-schema.org/draft/2020-12/schema",
"properties": {
"input": {
"additionalProperties": false,
"properties": {
"method": {
"enum": [
"GET"
],
"type": "string"
},
"queryParams": {
"properties": {
"prevalence_percent": {
"description": "How common the condition is, percent",
"type": "string"
},
"sensitivity_percent": {
"description": "True positive rate, percent",
"type": "string"
},
"specificity_percent": {
"description": "True negative rate, percent",
"type": "string"
}
},
"required": [
"prevalence_percent",
"sensitivity_percent",
"specificity_percent"
],
"type": "object"
},
"type": {
"const": "http",
"type": "string"
}
},
"required": [
"type",
"method"
],
"type": "object"
},
"output": {
"properties": {
"example": {
"properties": {
"confusion_matrix": {
"description": "Confusion matrix",
"type": "object"
},
"false_discovery_percent": {
"description": "False discovery, as a percentage",
"type": [
"number",
"null"
]
},
"inputs": {
"description": "Inputs after validation, as percentages and the population size",
"properties": {
"population": {
"description": "Population size used for the confusion matrix",
"type": [
"number",
"null"
]
},
"prevalence_percent": {
"description": "Prevalence, as a percentage",
"type": [
"number",
"null"
]
},
"sensitivity_percent": {
"description": "Sensitivity, as a percentage",
"type": [
"number",
"null"
]
},
"specificity_percent": {
"description": "Specificity, as a percentage",
"type": [
"number",
"null"
]
}
},
"type": "object"
},
"negative_likelihood_ratio": {
"description": "Negative likelihood ratio",
"type": [
"number",
"null"
]
},
"negative_predictive_value_percent": {
"description": "Negative predictive value, as a percentage",
"type": [
"number",
"null"
]
},
"note": {
"description": "Caveat or context for reading the result",
"type": "string"
},
"plain_language": {
"description": "Plain language",
"type": [
"string",
"null"
]
},
"positive_likelihood_ratio": {
"description": "Positive likelihood ratio",
"type": [
"number",
"null"
]
},
"positive_predictive_value_percent": {
"description": "Positive predictive value, as a percentage",
"type": [
"number",
"null"
]
},
"probability_disease_given_negative_percent": {
"description": "Probability disease given negative, as a percentage",
"type": [
"number",
"null"
]
},
"probability_of_positive_test_percent": {
"description": "Probability of positive test, as a percentage",
"type": "number"
},
"source": {
"description": "Data source the values come from",
"type": "string"
}
},
"required": [
"inputs",
"positive_predictive_value_percent"
],
"type": "object"
},
"type": {
"const": "json",
"type": "string"
}
},
"required": [
"type"
],
"type": "object"
}
},
"required": [
"input"
],
"type": "object"
}