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Table 3 Parameters of the dual Gauss, Gauss-Weibull, and Weibull-Gauss distribution models for the overall sample

From: The distribution of autistic traits across the autism spectrum: evidence for discontinuous dimensional subpopulations underlying the autism continuum

Parameter Result* Mean* Bootstrap: 95% confidence interval
Lower bound Upper bound
Model 4: Gauss + Gauss** (N = 4717) -Log-likelihood = 17,272.30
 Mean (μ1) 16.14 16.12 15.18 17.07
 Std. dev. (σ1) 6.06 6.06 5.57 6.60
 Weight (w) 0.74 0.74 0.65 0.81
 Threshold (θ) 27.30 27.30 24.40 30.35
 Mean (μ2) 34.19 34.17 30.87 37.20
 Std. dev. (σ2) 7.50 7.48 6.11 8.74
Model 5: Gauss + Weibull (N = 4717) -Log-likelihood = 17,261.31
 Scale (μ) 16.24 16.18 15.10 16.91
 Shape (σ) 6.15 6.13 5.56 6.57
 Weight (w) 0.26 0.27 0.20 0.37
 Threshold (θ) 27.70 27.56 24.10 30.05
 Scale (η) 38.08 37.93 34.48 40.15
 Shape (β) 5.18 5.19 3.88 6.41
Model 6: Weibull + Gauss -Log-likelihood = 17,229.37
 Scale (η) 20.92 20.88 20.05 21.57
 Shape (β) 2.85 2.86 2.74 3.00
 Weight (w) 0.85 0.85 0.80 0.88
 Threshold (θ) 32.70 32.60 30.00 34.70
 Mean (μ) 38.83 38.73 36.58 40.27
 Std. dev. (σ) 5.25 5.28 4.44 6.32
  1. *The result column shows the parameter values from the sample with the highest likelihood in the original data. The mean column shows the average parameter value from the 1000 resamples
  2. **μ1 and σ1, and μ2 and σ2 correspond to the parameters of Guass1 and Gauss2 distributions depicted in Fig. 3b