Chances of Getting Pregnant After Sex/Data: Difference between revisions
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* [https://www.nejm.org/doi/full/10.1056/nejm199512073332301 Peak Conception Probability (A)]: 0.33 | * [https://www.nejm.org/doi/full/10.1056/nejm199512073332301 Peak Conception Probability (A)]: 0.33 | ||
* [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC27529/ Fertile Window Width (σ, in days)]: 2.5 | * [https://www.ncbi.nlm.nih.gov/pmc/articles/PMC27529/ Fertile Window Width (σ, in days)]: 2.5 | ||
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== Risk Models == | == Risk Models == | ||
This model uses a Gaussian (bell curve) function to estimate risk | This model uses a Gaussian (bell curve) function to estimate risk. | ||
<riskmodel name="PregnancyRiskPerEvent"> | <riskmodel name="PregnancyRiskPerEvent"> | ||
{{PregnancyResult | {{PregnancyResult | ||
|{{#expr: 0.33 * (e ^ (-0.5 * (({timing_intercourse_day_x} - {cycle_ovulation_day_mu}) / 2.5) ^ 2)) * {age_multiplier} * (({bc_typical_mult} * {logic_typical}) + ({bc_perfect_mult} * {logic_perfect}) + ({bc_failed_mult} * {logic_failed})) }} | |{{#expr: 0.33*(e^(-0.5*(({timing_intercourse_day_x}-{cycle_ovulation_day_mu})/2.5)^2))*{age_multiplier}*( ({bc_typical_mult}*{logic_typical})+({bc_perfect_mult}*{logic_perfect})+({bc_failed_mult}*{logic_failed}) ) }} | ||
|{{#expr: 0.33 * {age_multiplier} * (( {bc_typical_mult} * {logic_typical} ) + ( {bc_perfect_mult} * {logic_perfect} ) + ( {bc_failed_mult} * {logic_failed} )) }} | |{{#expr: 0.33*{age_multiplier}*( ({bc_typical_mult}*{logic_typical})+({bc_perfect_mult}*{logic_perfect})+({bc_failed_mult}*{logic_failed}) ) }} | ||
{pagestate} | |{pagestate} | ||
}} | }} | ||
</riskmodel> | </riskmodel> | ||
''Calculation Explanation:'' 🔢 This model calculates the distance in days between intercourse (`x`) and the estimated day of ovulation (`μ`), then inputs that distance into a bell curve formula to find the corresponding probability. This result is then adjusted by the '''age_multiplier'''. This method more accurately reflects the rise and fall of fertility throughout the cycle. | ''Calculation Explanation:'' 🔢 This model calculates the distance in days between intercourse (`x`) and the estimated day of ovulation (`μ`), then inputs that distance into a bell curve formula to find the corresponding probability. This result is then adjusted by the '''age_multiplier'''. This method more accurately reflects the rise and fall of fertility throughout the cycle. | ||
If the exact timing isn't known, the maximum fertility adjusted for age (0.33 * age_multiplier) times the birth control effectiveness factor will be shown instead. | |||
---- | ---- | ||
Initially created by Gemini (Sept. 2025). | Initially created by Gemini (Sept. 2025). |
Latest revision as of 06:01, 18 September 2025
This subpage contains the data and risk models used on the main page. The data is based on population averages and is used to generate a risk estimate.
Baseline Fertility Parameters
These are single-value constants used in the risk model calculation. The descriptions are linked to the primary sources.
Age-Related Fertility
This table provides a final multiplier based on the woman's age, which adjusts the overall result from the bell curve calculation.
age_description | age_multiplier |
---|---|
Under 25 |
1.0 |
25-30 |
0.9 |
31-39 |
0.65 |
40 and over |
0.25 |
- Reference: Age and Fertility, American Society for Reproductive Medicine (ASRM), 2021.
Menstrual Cycle Profile
This table provides the estimated peak ovulation day (μ) for different cycle profiles. A value of -1 indicates an irregular cycle where a peak cannot be reliably predicted.
cycle_description | cycle_ovulation_day_mu |
---|---|
Regular and short (25 days or less) |
11 |
Regular and average (26-31 days) |
14 |
Regular and long (32 days or more) |
18 |
Irregular or I don't know |
-1 |
- Reference: Your Menstrual Cycle, Office on Women's Health, U.S. Department of Health & Human Services, 2021.
Timing of Intercourse
This table converts the user's time window into a single day of the cycle (x) for use in the calculation (using the midpoint of the range).
timing_description | timing_intercourse_day_x |
---|---|
Don't know/unsure |
-1 |
1-7 days (During or just after my period) |
4 |
8-13 days (About a week after my period) |
11 |
14-20 days (About two weeks after my period) |
17 |
21-28 days (In the week my next period was due) |
25 |
More than 28 days |
-1 |
- Reference: Based on standard menstrual cycle phases.
Contraception Use Case Logic
This table provides mutually exclusive multipliers to simulate conditional logic. Selecting a row sets one multiplier to 1 and the others to 0.
logic_description | logic_typical | logic_perfect | logic_failed |
---|---|---|---|
Unsure (Typical Use) |
1 |
0 |
0 |
It was used correctly (Perfect Use) |
0 |
1 |
0 |
It broke / there was a mistake (Failed Use) |
0 |
0 |
1 |
Contraception Method
This table provides the failure rates for typical, perfect, and failed use cases for each method. A value of 1.0 means no risk reduction.
bc_description | bc_typical_mult | bc_perfect_mult | bc_failed_mult |
---|---|---|---|
None (unprotected sex) |
1.0 |
1.0 |
1.0 |
Male Condom |
0.13 |
0.02 |
1.0 |
The Pill (combined) |
0.07 |
0.003 |
1.0 |
Withdrawal ("pulling out") |
0.22 |
0.04 |
1.0 |
Hormonal IUD (Mirena, etc.) |
0.002 |
0.002 |
1.0 |
Copper IUD (Paragard) |
0.008 |
0.008 |
1.0 |
The Implant (Nexplanon) |
0.001 |
0.001 |
1.0 |
The Shot (Depo-Provera) |
0.04 |
0.006 |
1.0 |
- Reference: Contraception, U.S. Centers for Disease Control and Prevention (CDC).
Risk Models
This model uses a Gaussian (bell curve) function to estimate risk.
RiskModel: Chances of Getting Pregnant After Sex/Data:PregnancyRiskPerEvent Content: {{PregnancyResult |{{#expr: 0.33*(e^(-0.5*(({timing_intercourse_day_x}-{cycle_ovulation_day_mu})/2.5)^2))*{age_multiplier}*( ({bc_typical_mult}*{logic_typical})+({bc_perfect_mult}*{logic_perfect})+({bc_failed_mult}*{logic_failed}) ) }} |{{#expr: 0.33*{age_multiplier}*( ({bc_typical_mult}*{logic_typical})+({bc_perfect_mult}*{logic_perfect})+({bc_failed_mult}*{logic_failed}) ) }} |{pagestate} }}
Calculation Explanation: 🔢 This model calculates the distance in days between intercourse (`x`) and the estimated day of ovulation (`μ`), then inputs that distance into a bell curve formula to find the corresponding probability. This result is then adjusted by the age_multiplier. This method more accurately reflects the rise and fall of fertility throughout the cycle.
If the exact timing isn't known, the maximum fertility adjusted for age (0.33 * age_multiplier) times the birth control effectiveness factor will be shown instead.
Initially created by Gemini (Sept. 2025).