Candice Lewis provided an example of a two sample t-test ...



These examples were provided by previous students in PSYC 6430. They are better for illustrating how not to write up the t test results than for showing how properly to do it. If you happen to come across a more recent article where t test results are well presented, do me a favour and send it my way. Thanks.Examples of Published Research with Analysis Including a Two-Sample Comparison of Means Using the t StatisticThe Health Status of Southern Children: A Neglected Regional DisparityJeffrey Goldhagen, Radley Remo, Thomas Bryant III, Peter Wludyka, Amy DaileyDavid Wood, Graham Watts and William LivingoodPediatrics 2005; 116; e746; Subjects: The subjects were American children in all fifty states.Variables Studied: (1) Children’s health status as operationalized by Child Health Index (CHI) scores. Each state was given a standard composite score (CHI) based on their infant mortality rate and several other outcome measurements. (2) Regional grouping of states. Design: Non-experimental. Existing data were obtained regarding a number of child health outcome measurements which were combined to create the CHI scores for children in each of the American states. Geographical regions were then created and their composite CHI scores were compared to ascertain if there was a spatial component to the issue of children’s health. Conclusions: Children in the Deep South were significantly more likely to have low CHI scores than children from other regions in the country. In fact, their aggregate CHI score is >1 standard deviation lower than the country’s mean CHI score.Quote: “The findings of this study indicate that region of residence in the United States is statistically related to important measures of children’s health and may be among the most powerful predictors of child health outcomes and disparities…. Mapping was used to redefine regional groupings of states, and parametric tests (2-sample t test, etc…) were used to compare the means of the CHI scores for the regional groupings and test for statistical significance.” (see Table 1).TABLE 1. Comparison of Composite Health Index Scores ofDeep South to the Remaining States in the Census Bureau–DefinedSouthRegionNo. of StatesHealth Score Mean95% CIt scorepDeep South9-1.4774-1.9378, -1.0170-3.9910001Rest of South7-0.3089-.5714, -.0464Group standard deviations were not provided.Cohen’s d with confidence interval should have been provided.Ford D. Y., and Harris, J.J. (1997). A study of the racial identity and achievement of black males and females, Roeper Review, 20, 105-110.There were 149 participants (54 male participants and 95 female participants). The participants were black students in grades 6 through grade 9. One of the questions asked was, “How do black males and females differ in their racial identities?” The variables studied were gender and racial identity. Ford and Harris (1997) used the revised Racial Identity Scale for Black Students (RIS) to assess students’ racial identity. The RIS was administered to all of the students. The revised scale contained 24 Likert-type questions (strongly agree = 4 to strongly disagree = 1). The RIS is divided into four subscales: pre-encounter, encounter, immersion-emersion, and internalization.The pre-encounter subscale contained 5 items such as: I am ashamed to be an African American, sometimes I feel like other students do not like me because I am African American. The encounter subscale contained eight items such as: I try to learn more about African Americans by talking to other people about my heritage, I am determined to find my Black identity. The immersion-emersion subscale contained eight items such as: Black is beautiful, My future is tied to the future of other Blacks. The internalization subscale contained three items such as everybody should learn about the cultures of other groups.A mean of 2.0 was found for the pre-encounter subscale which means the students did not agree with these items. According to the t test, both male participants and female participants had a mean of 2.0 on this sub-scale, therefore the results were not significantly different. A mean of 2.8 was found on the encounter sub-scale. Male participants and female participants had the same mean (2.8), so the results were not statistically significant and students tended to agree with items in the encounter sub-scale. Results of the immersion-emersion t test revealed significant gender difference (p < .05), with male participants having a higher response of 3.3. Female participants had a mean response of 3.1. The highest racial identity mean was 3.6 for the internalization sub-scale. According to the t test results, females had a significantly higher mean response of 3.7, compared to males, whose mean was 3.5, (p <. 05).As far as I can tell this is an appropriate example of an independent samples t test. I am assuming they used the appropriate t test for unequal sample sizes.1. The authors did not report the values of t and df.2. The authors used "males" and "females,” but “boys” and “girls” or “men” and “women” might not be appropriate give the age range of the subjects. Is a ninth grader a child or a young adult. Probably best here to use “male students” and “female students.” 3. The authors did not report exact p-values.4. The authors did not report the standard deviations. Without the standard deviations we cannot determine whether the significant effect reported here is trivial in magnitude or not. I suspect it is trivial. We also cannot determine whether the appropriate t test was employed (was there homogeneity of variance?).5. There certainly appears to be a lot of crap out there in the journals you all read.Chng, C., Carlon, A., & Toynes, B. (2006). HIV on historically black colleges and universities (HBCU): A study of five campuses in Texas, Oklahoma, Louisiana.?College Student Journal,?40(1), 25-34Subjects: The subjects were students at a private Historically Black College or UniversityVariables Studied: (1) Gender of Student (2) HIV knowledge.Design: Empirical Observational study. The researcher surveyed 1,146 students on their knowledge of HIV.Conclusions: Female students know more about HIV than Male studentsQuote: “As seen in Table 2, we found statistical significance for gender on the overall HIV knowledge scores where women scored higher than men (Men = 6.19, Women = 6.47, t(519) = -2.887, p? = .004). Statistically significant differences were also found in the following items, with women scoring higher: You can get HIV infection by deep kissing someone who has HIV (Men = .63, Women = .82, t(876.402) = -7.110, p? = .0005);Within group standard deviations should be given.Cohen’s d with CI should be given.Notice that at least once a separate variances t test was employed.The statistics provided in Table 2 do not match those presented in the text. ................
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