Assignment 1 Practical Data Management and Analysis for Public Health Graded Assignment 2 Posttest data from the “Don’t Just Sit There” evaluation in three high schools are finally available, and your...

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Assignment 1 Practical Data Management and Analysis for Public Health Graded Assignment 2 Posttest data from the “Don’t Just Sit There” evaluation in three high schools are finally available, and your assignment now is to analyze them. Before you begin, recall the following facts about the intervention itself and the evaluation design. The goal of the intervention is to reduce overweight and obesity in high school students. Components of the intervention are designed to increase self-efficacy for physical activity and value-expectancy for physical activity among participants. These, in turn, should lead to increased levels of physical activity and decreased incidence and prevalence of overweight and obesity. The evaluation is being carried out in three high schools. In each, 100 students were recruited and randomly assigned to either the intervention group or the control group. Baseline measures, including questionnaire-based assessments of self-efficacy and value-expectancy; an objective assessment of physical activity behavior via accelerometers; and objective assessments of height and weight, were collected prior to the intervention. The same measures were collected again six months after the intervention began. Thus, the evaluation uses a pretest-posttest control group design. Full data from the evaluation are available in the dataset Schools123PREPOST.sav. That dataset includes all raw data, plus derived variables including scale scores, computed BMI, and dichotomous and ordinal weight categorizations. The meaning of all variables should be clear from the codebook, DJSTprepostcodebook.doc. To determine whether the intervention was effective, use SPSS to carry out the following analyses. 1. Limiting your attention to members of the treatment group, determine whether and by how much self-efficacy, value-expectancy, physical activity, and BMI changed between pretest and posttest. 2. Still limiting your attention to members of the treatment group, determine whether there was any change between pretest and posttest in (a) the proportion of participants who were obese, and (b) the distribution of participants across the four weight categories: underweight, normal weight, overweight, and obese. 3. Next, ignore the pretest data and compare the treatment and control groups on the following posttest measures: self-efficacy, value-expectancy, physical activity, and BMI. 4. Compare the treatment and control groups in terms of (a) the proportion of participants who were obese at posttest; and (b) the distribution of participants across the four weight categories. 5. For each continuous posttest variable (i.e., self-efficacy, value-expectancy, physical activity, and BMI), carry out an analysis that incorporates the corresponding pretest variable into an examination of the effect of being in the treatment group versus the control group. 6. Administrators at one school, Clara Barton, are interested in sex-disaggregated effects of the intervention within that school. Carry out the analyses requested in Task 1 for (a) girls in Clara Barton and (b) boys in Clara Barton. Note that your analyses should be appropriate for the small sample sizes in these subgroups. 7. Likewise, carry out analyses requested in Task 3 for (a) girls in Clara Barton and (b) boys in Clara Barton, making sure that your analysis is appropriate to the small sample size. Prepare a written report summarizing the results of all of these analyses. For each analysis of each dependent variable, be sure to cover the magnitude and direction of the estimated effect, as well as its statistical significance. Your report should make clear whether, and in what ways, the evaluation data provide support for the effectiveness of the intervention on increasing self- efficacy and/or value expectancy, increasing physical activity, and decreasing BMI. There are two deliverables for this assignment: (1) An SPSS syntax file that accomplishes Tasks 1 through 7. The file should contain all of the commands necessary for accomplishing these tasks, in the specified order, and should not contain any extraneous commands. (2) Your written report summarizing the results. The report should integrate narrative text with results in tabular form. Please do not copy-and-paste SPSS into the report, but rather prepare your own tables. 1 CODEBOOK for StudentData.sav POS VAR NAME VARIABLE LABEL, VALUES, AND VALUE LABELS 1 ID Participant ID 2 SCHOOL Participant’s school 1 Clara Barton High School 2 Frederick Douglas High School 3 Harvey Milk High School 3 MALE Participant’s sex 0 Female 1 Male 4 RACE Participant’s race/ethnicity 1 Non-Hispanic White 2 Non-Hispanic Black 3 Hispanic or Latino 4 Other 5 GRADE Participant’s grade Write in grade (9, 10, 11, or 12) 6 A1pre It would help me cope with stress PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 7 A2pre It would be fun PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 8 A3pre It would help me make new friends PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 9 A4pre It would get or keep me in shape PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 10 A5pre It would make me more attractive PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 11 A6pre It would give me more energy PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 12 A7pre It would make me hot and sweaty PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 13 A8pre It would make me better in sports or other activities PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 14 B1pre I can be physically active during my free time on most days PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 15 B2pre I can ask my parent or other adult to do physically active things with me PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 16 B3pre I can be physically active during my free time on most days even if I could watch TV or play video games instead PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 17 B4pre I can be physically active during my free time on most days even if it is very hot or cold outside PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 18 B5pre I can ask my best friend to be physically active with me during my free time on most days PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 19 B6pre I can be physically active during my free time on most days even if I have to stay at home PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 20 B7pre I have the coordination I need to be physically active during my free time PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 21 B8pre I can be physically active during my free time on most days no matter how busy my day is PRE 1 Strongly Disagree 2 Disagree 3 Neutral 4 Agree 5 Strongly Agree 22 C1pre Value of coping well with stress PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 23 C2pre Value of having fun PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 24 C3pre Value of making new friends PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 25 C4pre Value of being in shape PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 26 C5pre Value of being attractive PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 27 C6pre Value of having plenty of energy PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 28 C7pre Value of getting hot and sweaty PRE -1.0 Very Negative -0.5 Negative 0 Neutral 0.5 Positive 1.0 Very Positive 29 C8pre Value of being good at sports or other
Answered 3 days AfterMay 13, 2021

Answer To: Assignment 1 Practical Data Management and Analysis for Public Health Graded Assignment 2 Posttest...

Anu answered on May 16 2021
139 Votes
Self-efficacy
Table 1, represents the results of paired t-test. From this table we can see that p-value (sig.) < 0.05 that mean null hypothesis (average value of self efficacy pre and self efficacy post is equal) is rejected. Now we move with the alternative hypothesis (average value of self efficacy pre and self efficacy post is not equal). Therefore we can say that the intervention is effective in the case of self efficacy.
Table 1: Pared t-test for Self efficacy in treatment group
    Treatment group
    Mean
    Std. Deviation
    Std. Error Mean
    t
    df
    Sig. (2-tailed)
    SEpret - SEpostt
    -0.60081
    0.81634
    0.
06557
    -9.163
    154
    0.000
Value Expectancy
Table 2, represents the results of paired t-test. From this table we can see that p-value (sig.) > 0.05 that mean null hypothesis (average value of Value expectancy pre and Value expectancy post is equal) is not rejected. Now we can not move with the alternative hypothesis (average value of self efficacy pre and self efficacy post is not equal). Therefore we can say that the intervention is not effective in the case of Value expectancy.
Table 2: Pared t-test for Value Expectancy in treatment group
    Treatment group
    Mean
    Std. Deviation
    Std. Error Mean
    t
    df
    Sig. (2-tailed)
    VEpret - VEpostt
    -0.17742
    1.19288
    0.09581
    -1.852
    154
    0.066
BMI
Table 3, represents the results of paired t-test. From this table we can see that p-value (sig.) > 0.05 that mean null hypothesis (average value of BMI pre and BMI post is equal) is not rejected. Now we can not move with the alternative hypothesis (average value of BMI pre and BMI post is not equal). Therefore we can say that the intervention is not effective in the case of BMI.
Table 3: Pared t-test for BMI in treatment group
    Treatment group
    Mean
    Std. Deviation
    Std. Error Mean
    t
    df
    Sig. (2-tailed)
    BMIpret - BMIpostt
    0.45653
    4.10193
    0.32948
    1.386
    154
    0.168
Physical Activity
Table 4, represents the results of paired t-test. From this table we can see that p-value (sig.) > 0.05 that mean null hypothesis (average value of physical activity pre and physical activity post is equal) is not rejected. Now we can not move with the alternative hypothesis (average value of physical activity pre and physical activity post is not equal). Therefore we can say that the intervention is not effective in the case of physical activity.
Table 4: Pared t-test for Physical Activity in treatment group
    Treatment group
    Mean
    Std. Deviation
    Std. Error Mean
    t
    df
    Sig. (2-tailed)
    PHYSACTpret - PHYSACTpostt
    -83.45680
    178.92341
    14.37147
    -5.807
    154
    0.000
OBESE
Table 5, represents the results of paired t-test. From this table we can see that p-value (sig.) > 0.05 that mean null hypothesis (average value of OBESE pre and OBESE post is equal) is not rejected. Now we can not move with the alternative hypothesis (average value of OBESE pre and OBESE post is not equal). Therefore we can say that the intervention is not effective in the case of OBESE.
Table 5: Pared t-test for OBESE in treatment group
    Treatment group
    Mean
    Std. Deviation
    Std. Error Mean
    t
    df
    Sig. (2-tailed)
    OBESEpret - OBESEpostt
    -0.03226
    0.36785
    0.02955
    -1.092
    154
    0.277
WGTGRP
Table 6, represents the results of paired t-test. From this table we can see that p-value (sig.) > 0.05 that mean null hypothesis (average value of WGTGRP pre and WGTGRP post is equal) is not rejected. Now we can not move with the alternative hypothesis (average value of WGTGRP pre and WGTGRP post is not equal). Therefore we can say that the intervention is not effective in the case of WGTGRP.
Table 6: Pared t-test for WGTGRP in treatment group
    Treatment group
    Mean
    Std. Deviation
    Std. Error Mean
    t
    df
    Sig. (2-tailed)
    WGTGRPpret - WGTGRPpostt
    0.07097
    0.83829
    0.06733
    1.054
    154
    0.294
Value of expectancy post
Table 7 represents that the p-value > 0.05 that mean null hypothesis (average value of value of expectancy for control and treatment group is equal) is not to be rejected. Now we can not move with the alternative hypothesis (average value of value of expectancy for control and treatment group is not equal). Therefore, in case of post value expectancy, we can say that value of expectancy is not significantly different for treatment and control group.
Table 7: Independent t-test for Value of expectancy post
    
    t
    df
    Sig. (2-tailed)
    Mean Difference
    Std. Error Difference
    Value of Expectancy post
    -0.467
    298
    0.641
    -0.06289
    0.13472
Post Self efficacy
Table 8 represents that the p-value < 0.05 that mean null hypothesis (average value of Self efficacy for control and treatment group is equal) is rejected. Now we can move with the alternative hypothesis (average value of Self efficacy for control and treatment group is not equal). Therefore, in case of post Self efficacy, we can say that Self efficacy is significantly different for treatment and control group.
Table 8: Independent t-test for Self efficacy post
    
    t
    df
    Sig. (2-tailed)
    Mean Difference
    Std. Error Difference
    Self efficacy post
    -7.093
    298
    0
    -0.65203
    0.09193
Post BMI
Table 9 represents that the p-value < 0.05 that mean null hypothesis (average value of BMI for control and treatment group is equal) is rejected. Now we can move with the alternative hypothesis (average value of BMI for control and treatment group is not equal). Therefore, in case of post BMI, we can say that BMI is significantly different for treatment and control group.
Table 9: Independent t-test for BMI post
    
    t
    df
    Sig. (2-tailed)
    Mean Difference
    Std. Error Difference
    Post BMI
    2.074
    298
    0.039
    1.03146
    0.49735
PHYSACT Post
Table 10 represents that the p-value < 0.05 that mean null hypothesis (average value of physical activity for control and treatment group is equal) is rejected. Now we can move with the alternative hypothesis (average value of physical activity for control and treatment group is not equal). Therefore, in case of post physical activity, we can say that physical activity is significantly different for treatment and control group.
Table 10: Independent t-test for physical...
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