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. 2022 Aug 3;79(9):889–898. doi: 10.1001/jamapsychiatry.2022.1947

Table 2. Twin Model Fit Statistics.

Model −2LLa Parameters df Δχ2b Δdfc P valued
Paranoia
Full bivariate 49 291.69 17 19 292 NA NA NA
Drop A moderation 49 293.00 16 19 293 1.32 1 .25
Drop C moderation 49 291.70 16 19 293 0.01 1 .91
Drop E moderation 49 292.59 16 19 293 0.90 1 .34
Drop all moderation 49 299.02 14 19 295 7.33 3 .06
Hallucinations
Full bivariate 49 578.99 17 19 302 NA NA NA
Drop A moderation 49 579.16 16 19 303 0.16 1 .69
Drop C moderation 49 579.00 16 19 303 0.00 1 .95
Drop E moderation 49 582.82 16 19 303 3.82 1 .05
Drop all moderation 49 588.62 14 19 305 9.63 3 .02
Cognitive disorganization
Full bivariate 49 476.53 17 19 291 NA NA NA
Drop A moderation 49 476.87 16 19 292 0.34 1 .56
Drop C moderation 49 476.53 16 19 292 0.00 1 <.99
Drop E moderation 49 488.19 16 19 292 11.66 1 .001
Drop all moderation 49 494.14 14 19 294 17.61 3 .001
Grandiosity
Full bivariate 49 509.94 17 19 246 NA NA NA
Drop A moderation 49 510.30 16 19 247 0.37 1 .55
Drop C moderation 49 511.65 16 19 247 1.71 1 .19
Drop E moderation 49 513.53 16 19 247 3.59 1 .06
Drop all moderation 49 518.32 14 19 249 8.38 3 .04
Anhedonia
Full bivariate 49 541.41 17 19 249 NA NA NA
Drop A moderation 49 541.43 16 19 250 0.01 1 .92
Drop C moderation 49 541.53 16 19 250 0.11 1 .74
Drop E moderation 49 548.50 16 19 250 7.09 1 .008
Drop all moderation 49 553.57 14 19 252 12.16 3 .007
Negative symptoms
Full bivariate 47 326.21 17 19 327 NA NA NA
Drop A moderation 47 326.96 16 19 328 0.75 1 .39
Drop C moderation 47 326.21 16 19 328 0.00 1 .99
Drop E moderation 47 326.65 16 19 328 0.44 1 .51
Drop all moderation 47 332.04 14 19 330 5.83 3 .12
APSS
Full bivariate 90 237.22 17 43 692 NA NA NA
Drop A moderation 90 237.77 16 43 693 0.55 1 .46
Drop C moderation 90 237.65 16 43 693 0.43 1 .51
Drop E moderation 90 244.17 16 43 693 6.95 1 .008
Drop all moderation 90 258.61 14 43 695 21.39 3 <.001

Abbreviation: NA, not applicable.

a

−2LL = fit statistic, −2 × log likelihood of the data.

b

Δχ2 = −2LL discrepancy between models, distributed χ2.

c

The difference in degrees of freedom between the 2 models is equivalent to the difference in number of parameters between 2 models.

d

Significant values indicate that a nested model fits statistically significantly more poorly than the model it is being compared to, supporting the statistical significance of the parameter(s) dropped from the model.