Assessment, Statistics, and Research

  Scale name: Self-Censorship Orientation (SCO) Scale overview: The Self-Censorship Orientation (SCO) is a 14-item scale designed to measure self-censorship, which the authors define as “intentionally and voluntarily withholding information from others in absence of formal obstacles.” Authors: Keren Sharvit et al. See the 2018 reference for the list of authors. Response Type: Items are rated on a scale of agreement from 1 = disagree to 4 = agree and 5 = undecided. Subscales and items   The authors identified two factors or subscales. 1. Self-censorship “ The first dimension, labeled “self-censorship”, reflects the tendency to conceal information that is seen as threatening.” (p. 347) Example: 1 I f I would encounter problematic conduct among my group members, I would feel responsible to bring that information to light. 2. Disclosure “ The second dimension, labeled “disclosure”, reflects the tendency to disseminate critical information.” Example: 9. People who

  Scale name: Christian Sociomoral Values Index Scale overview: This 13-item rating scale aims to measure the importance of select moral values commonly held among conservative Christians.   Response Type: Items are rated on a scale of agreement as follows: 1 = strongly disagree 2 = disagree 3 =   Neither Agree nor Disagree 4 = Agree 5 = Strongly agree Scale items = 13 1. All forms of birth control are sinful. 2. Birth control methods are acceptable if they do not cause an abortion. 3. Abortion is always sinful. 4. Premarital sex is always sinful. 5. Cohabitation is always sinful. 6. A biblical marriage is between one man and one woman. 7. Same-sex marriage is sinful. 8. Divorce is sinful. 9. Sexual orientation is a choice. 10. In a Christian marriage, a man and a woman submit to each other, but the man is always the head of the marriage. 11. Women have a vital role in Christian ministry, but they should not be priests or pastors. 12. Women have an important role

  A post hoc test is a statistical test used to determine if a pair of values are significantly different from each other after the primary analysis has been completed. The term post hoc is a Latin phrase meaning after the event. A common use of post hoc tests is the comparison of group means after an F -test in an ANOVA has revealed significant differences among the groups. The reason to test for differences after an overall test like ANOVA is to reduce the risk of finding a significant difference by chance. That is, if researchers perform a large number of tests on a sample, they may find one or more tests significant by chance. There are many post hoc tests. Following are some examples of tests that compare the means of two groups. Bonferroni Test This is a popular test. By dividing the significance level by the number of comparisons, the risk of finding a significant difference by chance is reduced. This procedure is called the Bonferroni Correction. Tukey's Honest Significant