We believed positive experiences with homosexual men and women would decrease participants’ negative attitudes toward gay men and lesbians. We found a moderately strong negative association (?=-.45, se = .07, p < .05) between quality of participants' interactions with gay and lesbian individuals and negative attitudes toward homosexual; thus, confirming our third hypothesis. A one unit increase in participants perceived positive experiences during their interactions with homosexual men and women decreased their sexual prejudice score by half a point. Moreover, we found significant correlations between positive experiences with gay men and lesbians and previous interactions with homosexual men and women (r = .26, se = .05, p < .05), as well as with participants' perceived similarities in their friends' attitudes toward gay men and lesbians (r = .24, se = .07, p < .05). While moderately low, the association between these three latent factors point to the multifaceted nature of participants' attitudes toward gay and lesbian people.
Our fourth hypothesis stated participants with stronger religious convictions would hold stronger negative attitudes toward gay men and lesbians. We found religiosity to be the strongest predictor of participants’ negative attitudes toward gay men and lesbians (?=.50, se = .11, p < .05). For every unit increase in participants' assessment of the importance of their religious beliefs in their lives, their sexual prejudice score increased by half a scale point.
The conclusions highly recommend no differences in this new model’s roadway are very different owed so you can participants’ sex
Given the low-tall prediction of peers’ parallels within their attitudes towards the homosexuals, i attempted deleting that it highway however the design are incapable of gather acceptably after 500 iterations. Thus, we leftover it cause for the model to be sure successful model balance. The very last design demonstrated an enthusiastic R dos regarding 56% for sexual prejudice’s difference.
Assessment getting sex consequences
In order to test whether the exploratory structural model provided an equally good fit for males and females, we re-ran the structural model estimation procedures running each group’s covariance matrix simultaneously. All factor loadings, paths, and variances were constrained to be equal in the initial model. The sex differences model indicated a relatively acceptable fit for both sexes, [? lovestruck dating apps 2 (141, N-males = 153, N-females = 207) = ; NFI = .88, NNFI = .93, CFI = .94, RMSEA = .055]. We then freed each path consecutively to test whether sex differences existed between the significant latent-factors and sexual prejudice. After freeing the path for participants’ interaction with homosexuals and sexual prejudice, we found no difference across male and female participants (? ? 2 (1) = 1.27, n.s.). Subsequently, we freed the path between positive experiences with homosexuals and sexual prejudice but we found no difference by participants’ sex (? ? 2 (1) = .05, n.s.). Finally, we tested whether sex differences existed between religiosity and sexual prejudice but no difference was found (? ? 2 (1)= 0.27, n.s.).
Regardless if our very own analyses find a good fit towards data, i checked if other model you will match the information exactly as really or better (MacCallum, Wegener, Uchino, & Fabrigar, 1993). Officially, it is just since the possible that folks that have better negative thinking with the homosexuality would stay away from getting together with homosexual men and you can lesbians, score their relationships because negative, perceiving their friends due to the fact that have other perceptions to the homosexual individuals, or discover support about their philosophy in their religiosity. Contour 2 gifts this inversed causation choice design lower than.
A choice exploratory structural model: Let’s say sexual bias forecasts telecommunications and you may self-confident event with homosexuals, sensed resemblance with peers’ perceptions into homosexuality, and you may religiosity. The solid lines represent mathematically extreme pathways in the .05 height. Magnitudes away from connection is actually presented with the high quality errors inside the parentheses; X dos (61, N = 360) = . Normed (NFI), non-normed (NNFI), and you can relative (CFI) goodness-of-match is .91, .91, .93, respectively; RMSEA was .09.