The 2025 4tran Survey

Jealous Cat's Analysis

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This page is written by Jealous Cat: Reddit

Introduction

This analysis is an attempt to answer 3 important questions:

Does starting age matter?
How much does time on HRT matter?
Does height matter?

Filters

Except where otherwise stated, the following filters are used:

Gender must be ‘Woman (MtF)’
Surgeries must be ‘No’
Age must be >= 16 and <=30
Starting age must be >= 10
Time on HRT must be >= 16
Respondents who did not answer the passing question were excluded

Passing Scale

The passing question was converted to a 4-point scale:

Gigapassoid and passoid were set to equal 4
Semipassoid was set to equal 3
Nonpassoid was set to equal 2
Gigahon was set to equal 1

Data

Summary Statistics

Tables

Uncategorised

	Mean	Median	SD
Age	21.87	21.00	3.15
Starting Age	19.88	19.50	2.92
Height (cm)	175.32	175.00	7.42
Time On HRT	1.99	1.50	1.66

By Starting Age

	Start Age Category	Mean	Median	SD
Age	Youngshit	17.74	17.50	1.781
	Midshit	19.78	19.00	1.946
	Lateshit	23.14	23.00	2.073
	Oldshit	27.47	27.00	1.515
Starting Age	Youngshit	15.12	15.40	1.116
	Midshit	17.75	17.80	0.870
	Lateshit	21.18	20.92	1.457
	Oldshit	25.95	25.50	1.446
Height (cm)	Youngshit	172.71	171.50	6.530
	Midshit	175.40	175.00	7.813
	Lateshit	175.36	175.00	7.176
	Oldshit	176.49	175.00	7.275
Time On HRT	Youngshit	2.61	2.10	2.571
	Midshit	2.03	1.50	1.682
	Lateshit	1.96	1.50	1.568
	Oldshit	1.52	1.50	0.943

By Passing Category

	4 Scale Passing Level	Mean	Median	SD
Age	Gigahon/Gigapoon	22.56	22.00	3.03
	Nonpassoid	21.26	21.00	2.94
	Semipassoid	22.17	22.00	3.31
	Passoid	22.33	22.00	3.16
Starting Age	Gigahon/Gigapoon	21.15	20.00	2.92
	Nonpassoid	19.84	19.50	2.82
	Semipassoid	19.77	19.36	2.96
	Passoid	19.29	19.00	2.83
Height(cm)	Gigahon/Gigapoon	177.58	175.00	8.15
	Nonpassoid	176.27	175.00	7.14
	Semipassoid	174.83	175.00	7.40
	Passoid	171.70	170.00	6.37
Time On HRT	Gigahon/Gigapoon	1.42	1.00	1.08
	Nonpassoid	1.42	1.00	1.35
	Semipassoid	2.41	2.00	1.80
	Passoid	3.04	2.64	1.62

Plots

Uncategorised

By Starting Age

By Passing Category

Model

Info

Model Info

Info
Model Type	Cumlative Link Model	Proportional odds logistic
Model	ordinal::clm	4 Scale Passing Level ~1 + Height (cm) + Time On HRT + Starting Age + Time on HRT-Start Age Interaction
Distribution	Logistic
Link function	Logit	Log of the odd of y
Direction	P(Y ≤ j)/P(Y > j)	j = Gigahon/Gigapoon \| Nonpassoid \| Semipassoid \| Passoid
Sample size	584
Converged	yes
C.I. method	Wald
Note. All covariates are centered to the mean

Results

Model Fit

R²	df	X²	p
0.0693	4	122	<.001

Additional Indices

Info	Model Value	Comment
Log Likelihood	-821
AIC	1656	Less is better
BIC	1688	Less is better
Deviance	1642	Less is better

Omnibus Tests

	X²	df	p
Height (cm)	25.36	1	<.001
Time On HRT	75.50	1	<.001
Starting Age	3.27	1	0.071
Time on HRT-Start Age Interaction	12.87	1	<.001

Parameter Estimates (Coefficients)

				95% CI			Exp(B) 95% CI
Name	Effect	Estimate	SE	LL	UL	Exp(B)	LL	UL	z	p
(Threshold)	Gigahon/Gigapoon\|Nonpassoid	-2.3534	.12748	-2.6033	-2.10359	.0950	.0740	.122	-18.46	<.001***
(Threshold)	Nonpassoid\|Semipassoid	-.1217	.07981	-.2781	.03475	.8854	.7572	1.035	-1.52	.127
(Threshold)	Semipassoid\|Passoid	2.1276	.12068	1.8911	2.36415	8.3948	6.6265	10.635	17.63	<.001***
Height (cm)	Height (cm)	-.0494	.00981	-.0686	-.03016	.9518	.9337	.970	-5.04	<.001***
Time On HRT	Time On HRT	.4338	.04993	.3360	.53167	1.5431	1.3993	1.702	8.69	<.001***
Starting Age	Starting Age	-.0446	.02467	-.0930	.00375	.9564	.9112	1.004	-1.81	.071
Time on HRT-Start Age Interaction	Time on HRT-Start Age Interaction	.0453	.01263	.0205	.07004	1.0463	1.0208	1.073	3.59	<.001***

From the model, we can conclude that there is a negative relationship between height and passing (p <.001). For every cm increase of height, the odds of being in a lower passing category increase by 4.82%. This can be seen by the height plot, which shows that all else equal, 175 cm is the point at which the likelihood of being a passoid or semipassoid intersect the likelihoods of being a nonpassoid or gigahon.

Additionally, time on HRT is positively correlated with passing (p <.001), to nobody’s surprise. For each year on HRT, the odds of being in a higher passing category increase by 54%. This is shown by the time on HRT plot, which show that chances of passing do indeed increase. This however does not directly account for starting age.

Starting age itself was found to not be a significant predictor of passing (p > 0.05). This makes sense, as time on HRT is more predictive. However, if one moderates the predictor of time on HRT by starting age, then the relationship becomes statistically significant (p <.001). The series of plots that compare passing and starting age after taking into account time on HRT show that a higher starting age may become less of a disadvantage with longer on HRT. It is worth noting that the model’s confidence decreases with more time on HRT, partially owing to a lack of data. In summary, starting age does not matter, time on HRT does. Unfortunately, height also matters, but with longer on HRT this disadvantage is reduced.