Practical Data Management and Analysis for Public Health Assignment 5
Graded Assignment 5
The results are in! The Gettin Out the Gunk intervention is complete, and post-intervention data have been collected from treatment and control group members and entered into our SPSS database. The tasks of cleaning and recoding the follow-up data, and the derivation of scale scores, are all complete. At last, we are ready to conduct statistical analyses to answer the question: “Did the intervention work?”
In attempting to answer that question, we will focus on four variables: knowledge, self-efficacy, and motivation scale scores, and, most importantly, actual LDL levels. For now, we will limit ourselves to studying continuous versions of these outcome variables.
Please download the GunkPrePost1.sav.dataset from the Practice Assignment 5 page of the Assignments section of this course.
Assignment
(1) To begin, pretend that no baseline (pre-intervention) data were collected. In other words, pretend that we have a posttest-only control group design. Conduct an appropriate conventional (i.e., parametric) statistical test of the null hypothesis of no intervention effect on knowledge scale scores. Repeat this analysis for self-efficacy scale scores, motivation scale scores, and actual LDL levels.
(2) Given that the sample size here is not huge, conventional statistical hypothesis tests could produce misleading results if certain assumptions – especially, the assumption that dependent variables are normally distributed – are not met. Therefore, for each of the four analyses in (1) above, please conduct an appropriate corresponding non-parametric statistical test of the null hypothesis of no intervention effect. How do the statistical conclusions compare to those obtained via the conventional tests?
(3) Next, pretend that there is no control group. In other words, limit your analysis to participants who were assigned to the treatment group (i.e., treat=1), and analyze the data as if they were obtained via a one-group pretest-posttest design. Conduct an appropriate conventional (i.e., parametric) statistical test of the null hypothesis of no intervention effect on knowledge scale scores. Repeat this analysis for self-efficacy scale scores, motivation scale scores, and actual LDL levels.
(4) Again, given that the sample size is not huge, conventional statistical hypothesis tests could be misleading if the assumption of normality is violated. Therefore, for each of the four analyses in (3), please conduct an appropriate corresponding non-parametric statistical test of the null hypothesis of no intervention effect. How do the statistical conclusions compare to those obtained via conventional scale scores?
(5) Now, use all the data: pretest and posttest, treatment and control groups. That is, analyze the data as if they were (as they in fact were, in our imagination) obtained via a pretest-posttest control group design. For each outcome, we can increase our statistical power by incorporating pre-intervention measures of that outcome into the analysis. Conduct an appropriate conventional (i.e., parametric) statistical test of the null hypothesis of no intervention effect on knowledge scale scores, taking into account our pre-intervention measure of knowledge. Repeat this analysis for self-efficacy scale scores, motivation scale scores, and actual LDL levels.
(6) Collect all of the results form (1) through (5) above into a written report with three sections. In the first section of the report, cover analyses (1) and (2); in the second section cover analyses (3) and (4); in the third section cover analysis (5). For each analysis, please report (a) how big the effect was in quantitative terms (e.g., how much higher in post-intervention knowledge scale scores were treatment group members, on average, compared to control group members?), and (b) whether or not the effect was statistically significant at the .05 level. Use your discretion as to whether or not to use tables to facilitate your presentation of the results.
Submission
In the Assignments section, please upload the following items to the Practice Assignment 5 page 24 hours before live session 5: 1. Your syntax file for carrying out the analyses requested in items (1) through (5) above; 2. Your written report as described in (6).
Buy Practical Data Management and Analysis for Public Health Assignment 5 Answers Online
Talk to our expert to get the help with Practical Data Management and Analysis for Public Health Assignment 5 to complete your assessment on time and boost your grades now
The main aim/motive of the management assignment help services is to get connect with a greater number of students, and effectively help, and support them in getting completing their assignments the students also get find this a wonderful opportunity where they could effectively learn more about their topics, as the experts also have the best team members with them in which all the members effectively support each other to get complete their diploma assignments. They complete the assessments of the students in an appropriate manner and deliver them back to the students before the due date of the assignment so that the students could timely submit this, and can score higher marks. The experts of the assignment help services at urgenthomework.com are so much skilled, capable, talented, and experienced in their field of programming homework help writing assignments, so, for this, they can effectively write the best economics assignment help services.
Get Online Support for Practical Data Management and Analysis for Public Health Assignment 5 Help Online
Resources
- 24 x 7 Availability.
- Trained and Certified Experts.
- Deadline Guaranteed.
- Plagiarism Free.
- Privacy Guaranteed.
- Free download.
- Online help for all project.
- Homework Help Services
