Table 3.

Primary outcomes: PR vs. MR

		Effect			p value
Outcome	Control mean	Unconditional	Conditional	Asymptotic	Naïve permutation	Conditional permutation	Conditional permutation (adj.)
Males
Prevalence of stereotypy	0.215	0.441	0.470	0.000	0.000	0.000	0.000
Frequency of stereotypy	0.046	0.300	0.287	0.000	0.000	0.000	0.000
Prevalence of illness	0.723	−0.004	0.004	0.482	0.566	0.415	0.415
Frequency of illness	0.154	0.016	0.021	0.334	0.330	0.229	0.626
Prevalence of wound	0.385	0.053	0.042	0.313	0.389	0.380	0.692
Frequency of wound	0.052	0.045	0.044	0.111	0.082	0.097	0.478
Prevalence of alopecia	0.369	−0.057	0.018	0.291	0.221	0.367	0.602
Frequency of alopecia	0.113	−0.047	−0.030	0.052	0.070	0.253	0.502
Females
Prevalence of stereotypy	0.070	0.770	0.751	0.000	0.000	0.000	0.000
Frequency of stereotypy	0.015	0.346	0.352	0.000	0.000	0.000	0.000
Prevalence of illness	0.649	0.071	0.058	0.264	0.192	0.318	0.318
Frequency of illness	0.161	−0.029	−0.027	0.202	0.218	0.257	0.503
Prevalence of wound	0.509	0.251	0.251	0.013	0.008	0.017	0.046
Frequency of wound	0.094	0.062	0.067	0.054	0.028	0.028	0.110
Prevalence of alopecia	0.403	0.316	0.261	0.004	0.002	0.012	0.024
Frequency of alopecia	0.137	0.116	0.104	0.014	0.010	0.006	0.017

n = 97 for males, and n = 82 for females. p values below 0.1 are in bold. Control is MR. Unconditional is unconditional difference in means between the treatment and control groups. The corresponding p values are computed in the columns asymptotic and naïve permutation. Conditional is conditional treatment effect with linear covariates year of birth and total time spent in the primate center. The corresponding p value is computed in the column conditional permutation. Asymptotic is one-sided p value for the hypothesis of no treatment effect based on asymptotic inference; the estimated effect size is in the unconditional column. Naïve permutation is the one-sided p value for the hypothesis of no treatment effect based on unconditional permutation inference; the estimated effect size is in the unconditional column. Conditional permutation is the one-sided p value for the hypothesis of no treatment effect based on the Freedman–Lane procedure using the linear covariates year of birth and total time spent in the primate center and restricting permutation orbits within strata formed by being a first- or later-born monkey; the estimated effect size is in the conditional column. Conditional permutation (adj.) is the p value from the previous column adjusted for multiple inferences using the step-down procedure.