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We calculated the coefficient for the product of the independent variable and the moderator (interaction term) and estimated the conditional effects of X on Y at each of the two values of the moderator, along with a standard error and p-value.
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The modest sample size, data loss to follow-up and the power limitations in testing for moderator interactions limit any conclusions about causality for or specificity between our findings and affective disorder.
Although we did not have explicit hypotheses regarding moderator interactions, such analyses would have been helpful to determine the combination of methodological parameters that maximize concordance; for example, what happens when women are exposed to varied stimulus content, visual stimuli, and their genital response is assessed using thermography?
In our study, we found a moderator-interaction effect (optimism) that affects the strength of the relation between a predictor variable (anxiety-trait) and an outcome variable (HRQOL) for some dimensions, in particular for the social dimension, which has never studied before.
Depending on the within twin correlation of the moderator, the interaction will arise as an A × E or A × C.
All analysis will be repeated considering age status (adult or child) as a moderator in interaction with the treatment group (control or intervention), allowing estimates of treatment effect in the subpopulations to be summarised.
In another situation, M may also modify the relation of X to Y such that the relation of X to Y differs at different values of M. This is referred to as a moderator or interaction effect (see MacKinnon et al. [ 18] and references therein).
The moderator encouraged interactions among the participants and ensured that each group fully discussed each study topic and that each participant had an adequate opportunity to express his or her views.
Similarly, follow-up models were tested using the various childhood abuse subtypes (physical/emotional/neglect, sexual) as the moderators; the interactions terms were statistically non-significant, although the graphical patterns appeared to be similar.
The moderator actively stimulated interaction and discussion between the participants.
Log-linear modeling for contingency tables was used to estimate main and interaction (moderator) effects independently.
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