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    Exercise 31 t- Test for Dependent Groups

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    The t-test for dependent groups is a parametric analysis technique used to determine statistical differences between two related samples or groups. Groups are dependent or related because they were matched as part of the design to ensure similarities between the two groups and thus reduce the effect of extraneous variables. For example, two groups might be matched on gender so an equal number of males and females are in each group, thus reducing the extraneous effect of gender on the study results. The researcher's decision to match groups is determined by the study being conducted and is detailed in the study design. In previous research, groups have most commonly been matched for age, gender, ethnicity, diagnoses, and status of illness. Matching the groups strengthens the study design by reducing the effect of extraneous variables controlled by matching. Groups are also dependent when scores used in the analysis are obtained from the same subjects under different conditions, such as pre-test and post-test study design. In this type of design, a single group of subjects is exposed to pre-test, treatment, and post-test. Subjects are referred to as serving as their own control during the pre-test that is then compared with the Post-test scores following the treatment. This is a weak quasi-experimental design since it is difficult to determine the effects of a treatment without comparison to a separate control group. The assumptions for the t-test for dependent groups are:

    1. The distribution of scores is normal or approximately normally distributed.
    2. The dependent variable(s) is (are) measured at interval or ratio levels.
    3. The groups examined for differences are dependent based on matching or subjects serving as their own control.
    4. The differences between the paired scores are independent (Burns & Grove, 2005).

    Source: Kim, C., Junes, K., & Song, R. (2003). Effects of a health-promotion program on cardiovascular risk factors, health behaviors, and life satisfaction in institutionalized elderly women. International Journal of Nursing Studies, 40 (4), 375-81.


    Kim, Junes, and Song (2003) conducted a quasi-experimental study with a one group pre-test post-test design. "A convenient sample of 21 elderly women was recruited from a home for elderly people." (Kim et al., 2000, p. 376). The purpose of the study was to determine the health benefits of a 3-month health-promotion program for institutionalized elderly women on cardiovascular risk factors, health behaviors, and life satisfaction. These researchers found the following positive effects from the program: reductions in total risk score, improved health behaviors, and improved life satisfaction. However, Kim et al. (2003) noted a decrease in these positive effects 3 months after the completion of the health-promotion program.

    Relevant Study Results

    A total of 25 women were enrolled in the health-promotion program and 21 subjects completed the program with three sets of outcome assessments at pre-test, 3 months, and 6 months. The mean age of the subjects was 77 years, and 90% of them had been diagnosed with one or more chronic diseases. The significance level of the study was set at ? = 0.05. The results from the study are presented in the two tables that follow. Table 2 describes the health-promotion program's effects on cardiovascular risk factors, and Table 3 describes the effects on health behaviors. The third dependent variable of this study was life satisfaction, which was significantly improved from pretest to the end of the health-promotion program at 3 months and at 6 months follow-up.

    TABLE 2 Program Effects on Cardiovascular Risk Factors

    (see attached file)

    EXERCISE 31 Questions

    1. What are the two groups whose results are reflected by the t ratios in Tables 2 and 3?

    2. Which t ratio in Table 2 represents the greatest relative or standardized difference between the pretest and 3 months outcomes? Is this t ratio statistically significant? Provide a rationale for your answer.

    3. Which t ratio listed in Table 3 represents the smallest relative difference between the pretest and 3 months? Is this t ratio statistically significant? What does this result mean?

    4. What are the assumptions for conducting a t-test for dependent groups in a study? Which of these assumptions do you think were met by this study?

    5. Compare the 3 months and 6 months t ratios for the variable Exercise from Table 3. What is your conclusion about the long-term effect of the health-promotion intervention on Exercise in this study?

    6. What is the smallest, significant t ratio listed in Table 2? Provide a rationale for your answer.

    7. Why are the larger t ratios more likely to be statistically significant?

    8. Did the health-promotion program have a statistically significant effect on Systolic blood pressure (BP) in this study? Provide a rationale for your answer.

    9. Examine the means and standard deviations for Systolic BP at pretest, 3 months (completion of the treatment), and 6 months. What do these results indicate? Are these results clinically important? Provide a rationale for your answer.

    10. Is this study design strong or weak? Provide a rationale for your answer.

    Would you, as a health care provider, implement this intervention at your facility based on the Total Risk Score results? Provide a rationale for your answer.

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