Ludwig et al. Supplementary data

Supplementary data

Text S1. Checking assumptions and validity of the regression model.

We checked the validity and the assumptions of the regression model as follows. To make sure multicollinearity was in an acceptable range, we checked whether all tolerance values were above .20, the maximum variance inflation factor (VIF) was not higher than 10, and the average VIF was not substantially higher than 1 (e.g., see Field, 2005; Menard, 1995). We further assessed the assumption of homoscedasticity by visual inspection of relevant plots (Field, 2005), and we checked whether residuals were normally distributed by visual inspection and by a Kolmogorov-Smirnoff test.

Independency of errors was assessed using the Durbin-Watson statistic (Durbin & Watson, 1951).

Finally, we checked for outliers and influential cases by looking for participants fulfilling any of the following criteria: absolute standardised residuals > 3, Cook’s distance > 1 (Cook & Weisberg, 1982), centred leverage values > 3 * (k+1)/n , DFBeta values > 1, or Mahalanobis distance > 15 (Barnett &

Lewis, 1978; Field, 2005).

Regression diagnostics indicated that the assumptions of multiple regression had been met and that the model was not influenced by a small number of cases. That is, multicollinearity was in a very acceptable range, there was no heteroscedasticity, residuals were normally distributed, and error terms were independent. Cook’s distances and DFBeta values were all in a very good range, and there were no outliers concerning the standardised residuals. The only issue arose for 3 participants who had high

Mahalanobis distances (> 15), indicating that they were multivariate outliers. Two of these cases also had centred leverage values three times higher than average, indicating that they had a relatively high influence on the model. When exploratively estimating the model again without these three cases, the same regressors were significant as before. Therefore the cases are not problematic for our conclusions.

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Text S2. Detailed explanation of the post-hoc procedures for the interaction of motor impulsivity x gender.

We used the standard recommended post-hoc procedures to explore the significant interaction of motor impulsivity x gender (Aiken & West, 1991, pp. 130-133; Richter, 2007; West, Aiken, &

Krull, 1996). We carried out four post-hoc tests in total and corrected for multiple comparisons using

Bonferroni-correction (corrected α = .013).

First, we determined if motor impulsivity is a significant predictor of hypnotic suggestibility for men and/or for women separately by calculating simple slopes for both genders. This was done by re-estimating the final model again twice using dummy-coding for gender (first, men were coded as 0 and women as 1, and second, women were coded as 0 and men as 1). In regression models containing an interaction, the single terms that are part of the interaction are conditional effects. That is, they hold true when the other variable involved in the interaction equals 0 (Hayes, Glynn, & Huge, 2012; West et al., 1996). Thus, when using dummy-coding for gender, the single term BIS-11 motor impulsivity is the effect of BIS-11 motor impulsivity for the group coded as 0 (Aiken & West, 1991; p. 131; Hayes et al., 2012; Richter, 2007). In this way it was possible to determine the effect of motor impulsivity on

HGSHS:A score for men and for women.

Second, we approached the interaction from the opposite perspective by determining the effect of gender at very low and very high levels of motor impulsivity (Aiken & West, 1991, pp. 132-133).

In our final model reported in the main text, the beta for the single term gender is the effect of gender for participants with an average level of motor impulsivity. This is due to centring of our regressors, which ensured that 0 on the motor impulsivity scale equals an average level of motor impulsivity. As noted above, the single terms that are part of the interaction hold true when the other variable involved in the interaction is 0. The fact that the single term gender was non-significant in our final model therefore means that gender had no effect for participants with an average level of motor impulsivity.

Another way of looking at this is that gender had – on average across all levels of motor impulsivity – no effect (West et al., 1996). For our post-hoc tests, we rescaled motor impulsivity before estimating the final model again (these times using dummy coding for gender) to determine the effect of gender

2 Ludwig et al. Supplementary data for participants very high and very low in motor impulsivity (Aiken & West, 1991, p. 132-133). In one analysis, motor impulsivity was scaled such that 0 was equivalent to the mean of motor impulsivity minus 2SD; and in the other analysis it was scaled such that 0 was equivalent to the mean of motor impulsivity plus 2SD. In this way it was possible to determine the effect of gender for participants with high and with low motor impulsivity.

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Table S1. Descriptive statistics arranged by gender concerning the average scores on the questionnaires.

Males Females Gender comparison

(n = 63) (n = 91) Questionnaire Mean SD Mean SD t(152) p Cohen’s d BSC 42.62 6.39 41.35 6.39 1.21 .23 -.20

SR 30.32 3.83 28.99 3.98 2.069 .04 -.34

BIS-11 Total 61.43 9.15 61.77 8.33 -0.24 .81 .04

- Attention 15.43 3.06 16.03 2.7 -1.292 .20 .21

- Motor 22.94 4.61 22.67 3.81 0.391 .70 -.06

- Non-Planning 23.06 4.16 23.07 4.22 -0.004 1.00 .00

HGSHS:A 6.13 2.74 6.63 2.4 -1.199 .23 .20

Note. SD: standard deviation. BSC: Brief Self-Control Scale. SR: Self-Regulation Scale. BIS-11:

Barratt Impulsiveness Scale. HGSHS:A: Harvard Group Scale of Hypnotic Susceptibility. None of the p-values survived Bonferroni-correction for multiple comparisons (α = .007). Note that also a multivariate ANOVA with the outcome variables BSC, SR, BIS-11 Attention, BIS-11 Motor, BIS-11

Non-Planning, and HGSHS:A did not reveal an effect of gender (p = .32).

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Table S2. Number of participants passing each individual suggestion arranged by gender.

Subjects passing suggestion Difference χ2(1) and Odds Suggestion Type of suggestion Men Women associated p ratio Postural alteration direct motor 65% 78% 3.14, p = .10 0.52 Eye closure direct motor 73% 70% 0.13, p = .86 1.14 Hand lowering direct motor 86% 90% 0.70, p = .45 0.66 Arm immobilization motor challenge/inhibition 48% 49% 0.05, p = .87 0.93 Finger lock motor challenge/inhibition 71% 63% 1.29, p = .30 1.49 Arm rigidity motor challenge/inhibition 49% 47% 0.06, p = .87 1.08 Hands moving direct motor 75% 84% 1.84, p = .22 0.58 Communication motor challenge/inhibition 46% 55% 1.18, p = .33 0.70 inhibition Hallucination factorially complex 17% 19% 0.04, p = 1.00 0.92 Eye catalepsy motor challenge/inhibition 40% 59% 5.76, p = .02 0.45 Post-hypnotic factorially complex 33% 46% 2.53, p = .13 0.58 suggestion Amnesia factorially complex 10% 2% 4.06, p = .06a 4.68

Note. Nmen = 63, Nwomen = 91. a: an assumption of the chi-square test was not met for this comparison, because expected frequencies in two cells of the contingency tables were lower than 5. P-values are two-tailed. No correlation survived Bonferroni-correction for multiple comparisons (α = .004). The comparison that is significant at an uncorrected level is marked in bold. The reported odds ratio is the odds ratio for passing a suggestion for men divided by the odds ratio for passing a suggestion for women.

Table S3. Point-biserial correlations of motor impulsivity with each individual suggestion for men and women separately.

Men (n = 63) Women (n = 91)

Suggestion Type of suggestion rpb p rpb p Postural alteration direct motor .17 .18 .07 .49 Eye closure direct motor .16 .22 .00 1.00 Hand lowering direct motor .19 .13 -.12 .27 Arm immobilization motor challenge/inhibition .29 .02 .05 .63 Finger lock motor challenge/inhibition .14 .26 -.01 .95 Arm rigidity motor challenge/inhibition .06 .63 -.03 .75 Hands moving direct motor .20 .12 -.15 .16 Communication motor challenge/inhibition .24 .06 .05 .64 inhibition Hallucination factorially complex .12 .36 -.03 .76 Eye catalepsy motor challenge/inhibition .30 .02 .13 .22

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Post-hypnotic factorially complex .18 .16 -.11 .32 suggestion Amnesia factorially complex .03 .83 -.15 .17 Note. None of the correlations survive Bonferroni-correction for multiple comparisons within groups

(α = .004). Correlations that are significant at an uncorrected level are marked in bold.

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Table S4. Point-biserial correlations of non-planning impulsivity with each individual suggestion for all subjects.

Suggestion Type of suggestion rpb p Postural alteration direct motor .12 .15 Eye closure direct motor -.04 .64 Hand lowering direct motor .16 .053 Arm immobilization motor challenge/inhibition .21 .009 Finger lock motor challenge/inhibition .14 .08 Arm rigidity motor challenge/inhibition .11 .18 Hands moving direct motor .11 .18 Communication inhibition motor challenge/inhibition .16 .045 Hallucination factorially complex -.04 .59 Eye catalepsy motor challenge/inhibition .21 .008 Post-hypnotic suggestion factorially complex .09 .28 Amnesia factorially complex .12 .15 Note. N = 154. None of the correlations survive Bonferroni-correction for multiple comparisons (α = .

004). Correlations that are significant at an uncorrected level are marked in bold.

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Table S5. Point-biserial correlations of the brief self-control scale with each individual suggestion for all subjects.

Suggestion Type of suggestion rpb p Postural alteration direct motor -.11 .18 Eye closure direct motor .02 .78 Hand lowering direct motor -.12 .16 Arm immobilization motor challenge/inhibition .05 .53 Finger lock motor challenge/inhibition .15 .07 Arm rigidity motor challenge/inhibition .11 .18 Hands moving direct motor -.05 .53 Communication inhibition motor challenge/inhibition .02 .84 Hallucination perceptual .01 .85 Eye catalepsy motor challenge/inhibition .00 .99 Post-hypnotic suggestion direct motor .03 .76 Amnesia cognitive -.01 .91 Note. N = 154.

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