Assessment, Statistics, and Research

  READING EXPERIMENTAL RESEARCH: QUESTIONS TO GUIDE YOUR ANALYSIS Geoffrey W. Sutton, Ph.D.   Use the following questions to help you read psychological experiments. With experience, the questions should become a natural part of your analysis.   Who are the authors? When was the study published? Where do the authors write? How do you contact the lead author? Which journal published the article? How was the research funded? What might the above situation suggest about the research? What was studied (variables)? Why was it studied (need, importance)? What theory or theories provide the context for the study? What have previous studies found? What was expected (purpose, hypotheses)? Whom (describe the participants)? Age Gender Ethnicity Other key variables How did the authors operationally define their variables? How to (what procedures were followed)? How did they control for possible confounding effects (internal validity)? How were

  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

In statistics, an effect size ( ES ) indicates the strength of the relationship between two variables. In psychological experiments, researchers are interested in the strength of the effect of the Independent Variable on the Dependent Variable. In psychotherapy studies, researchers may be interested in the effects of treatment on a measure of the dependent variable. A research questions may be framed: How effective is a set of 6 CBT sessions on the reduction of depression? Psychologists have often described effect sizes as small, medium, or large. Cohen's d Cohen's d is a measure of effect size between two groups. The mean of one group is subtracted from a second group and divided by the pooled standard deviation of the two groups. ES = (M1 - M2) / SD Effect Size  Label 0.2     Small 0.5     Medium 0.8     Large Pearson Correlation Coefficient ( r ) 0.1 to 0.3  Small 0.3 to 0.5  Medium 0.5 to 1.0   Large Converting Cohen's d to the correlation coefficient r =   d / √ d 2

  Factor Analysis and Assessment In testing, factor analysis is a mathematical strategy to analyze groups of items within a large test to see how well they relate to each other. The goal will be to reduce the large number of items to a set of factors that appear to measure different but related constructs; hence, factor analysis is a method of data reduction. (Sutton, 2020) A large test of various abilities may be analyzed for ways to group different abilities. Short tests of vocabulary, verbal analogies, and synonyms might form a factor that a researcher could label as "Verbal Abilities." A factor is a group of variables that are highly correlated with each other and, although different, they appear to have something in common. Researchers choose names for groups of variables based on the content of the variables in the factor. In large research projects, each participant may have scores on a large number of variables. Factor analysis can be used to identify patterns amo